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1 | import numpy,math,random,time | |
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2 | #---------------1 Heredamos JRODatareader | |
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3 | from schainpy.model.io.jroIO_base import * | |
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4 | #---------------2 Heredamos las propiedades de ProcessingUnit | |
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5 | from schainpy.model.proc.jroproc_base import ProcessingUnit,Operation,MPDecorator | |
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6 | #---------------3 Importaremos las clases BascicHeader, SystemHeader, RadarControlHeader, ProcessingHeader | |
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7 | from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader,SystemHeader,RadarControllerHeader, ProcessingHeader | |
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8 | #---------------4 Importaremos el objeto Voltge | |
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9 | from schainpy.model.data.jrodata import Voltage | |
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10 | ||
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11 | class SimulatorReader(JRODataReader, ProcessingUnit): | |
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12 | incIntFactor = 1 | |
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13 | nFFTPoints = 0 | |
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14 | FixPP_IncInt = 1 | |
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15 | FixRCP_IPP = 1000 | |
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16 | FixPP_CohInt = 1 | |
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17 | Tau_0 = 250 | |
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18 | AcqH0_0 = 70 | |
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19 | H0 = AcqH0_0 | |
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20 | AcqDH_0 = 1.25 | |
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21 | DH0 = AcqDH_0 | |
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22 | Bauds = 32 | |
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23 | BaudWidth = None | |
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24 | FixRCP_TXA = 40 | |
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25 | FixRCP_TXB = 70 | |
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26 | fAngle = 2.0*math.pi*(1/16) | |
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27 | DC_level = 500 | |
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28 | stdev = 8 | |
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29 | Num_Codes = 2 | |
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30 | #code0 = numpy.array([1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1]) | |
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31 | #code1 = numpy.array([1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0,1,1,1,0,0,0,1,0]) | |
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32 | #Dyn_snCode = numpy.array([Num_Codes,Bauds]) | |
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33 | Dyn_snCode = None | |
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34 | Samples = 200 | |
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35 | channels = 5 | |
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36 | pulses = None | |
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37 | Reference = None | |
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38 | pulse_size = None | |
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39 | prof_gen = None | |
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40 | Fdoppler = 100 | |
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41 | Hdoppler = 36 | |
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42 | Adoppler = 300 | |
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43 | frequency = 9345 | |
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44 | nTotalReadFiles = 1000 | |
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45 | ||
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46 | def __init__(self): | |
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47 | """ | |
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48 | Inicializador de la clases SimulatorReader para | |
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49 | generar datos de voltage simulados. | |
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50 | Input: | |
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51 | dataOut: Objeto de la clase Voltage. | |
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52 | Este Objeto sera utilizado apra almacenar | |
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53 | un perfil de datos cada vez qe se haga | |
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54 | un requerimiento (getData) | |
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55 | """ | |
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56 | ProcessingUnit.__init__(self) | |
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57 | print(" [ START ] init - Metodo Simulator Reader") | |
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58 | ||
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59 | self.isConfig = False | |
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60 | self.basicHeaderObj = BasicHeader(LOCALTIME) | |
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61 | self.systemHeaderObj = SystemHeader() | |
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62 | self.radarControllerHeaderObj = RadarControllerHeader() | |
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63 | self.processingHeaderObj = ProcessingHeader() | |
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64 | self.profileIndex = 2**32-1 | |
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65 | self.dataOut = Voltage() | |
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66 | #code0 = numpy.array([1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1]) | |
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67 | code0 = numpy.array([1,1,1,-1,1,1,-1,1,1,1,1,-1,-1,-1,1,-1,1,1,1,-1,1,1,-1,1,-1,-1,-1,1,1,1,-1,1]) | |
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68 | #code1 = numpy.array([1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0,1,1,1,0,0,0,1,0]) | |
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69 | code1 = numpy.array([1,1,1,-1,1,1,-1,1,1,1,1,-1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,1,-1,1,1,1,-1,-1,-1,1,-1]) | |
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70 | #self.Dyn_snCode = numpy.array([code0,code1]) | |
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71 | self.Dyn_snCode = None | |
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72 | ||
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73 | def set_kwargs(self, **kwargs): | |
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74 | for key, value in kwargs.items(): | |
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75 | setattr(self, key, value) | |
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76 | ||
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77 | def __hasNotDataInBuffer(self): | |
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78 | ||
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79 | if self.profileIndex >= self.processingHeaderObj.profilesPerBlock* self.nTxs: | |
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80 | if self.nReadBlocks>0: | |
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81 | tmp = self.dataOut.utctime | |
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82 | tmp_utc = int(self.dataOut.utctime) | |
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83 | tmp_milisecond = int((tmp-tmp_utc)*1000) | |
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84 | self.basicHeaderObj.utc = tmp_utc | |
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85 | self.basicHeaderObj.miliSecond= tmp_milisecond | |
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86 | return 1 | |
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87 | return 0 | |
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88 | ||
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89 | def setNextFile(self): | |
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90 | """Set the next file to be readed open it and parse de file header""" | |
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91 | ||
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92 | if (self.nReadBlocks >= self.processingHeaderObj.dataBlocksPerFile): | |
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93 | self.nReadFiles=self.nReadFiles+1 | |
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94 | if self.nReadFiles ==self.nTotalReadFiles: | |
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95 | self.flagNoMoreFiles=1 | |
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96 | raise schainpy.admin.SchainWarning('No more files to read') | |
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97 | ||
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98 | print('------------------- [Opening file] ------------------------------',self.nReadFiles) | |
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99 | self.nReadBlocks = 0 | |
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100 | ||
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101 | def __setNewBlock(self): | |
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102 | self.setNextFile() | |
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103 | if self.flagIsNewFile: | |
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104 | return 1 | |
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105 | ||
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106 | def readNextBlock(self): | |
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107 | while True: | |
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108 | self.__setNewBlock() | |
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109 | if not(self.readBlock()): | |
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110 | return 0 | |
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111 | self.getBasicHeader() | |
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112 | break | |
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113 | if self.verbose: | |
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114 | print("[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks, | |
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115 | self.processingHeaderObj.dataBlocksPerFile, | |
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116 | self.dataOut.datatime.ctime()) ) | |
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117 | return 1 | |
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118 | ||
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119 | def getFirstHeader(self): | |
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120 | self.getBasicHeader() | |
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121 | self.dataOut.processingHeaderObj = self.processingHeaderObj.copy() | |
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122 | self.dataOut.systemHeaderObj = self.systemHeaderObj.copy() | |
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123 | self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy() | |
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124 | ||
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125 | self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock | |
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126 | self.dataOut.heightList = numpy.arange(self.processingHeaderObj.nHeights) * self.processingHeaderObj.deltaHeight + self.processingHeaderObj.firstHeight | |
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127 | self.dataOut.channelList = list(range(self.systemHeaderObj.nChannels)) | |
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128 | self.dataOut.nCohInt = self.processingHeaderObj.nCohInt | |
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129 | # asumo q la data no esta decodificada | |
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130 | self.dataOut.flagDecodeData = self.processingHeaderObj.flag_decode | |
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131 | # asumo q la data no esta sin flip | |
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132 | self.dataOut.flagDeflipData = self.processingHeaderObj.flag_deflip | |
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133 | self.dataOut.flagShiftFFT = self.processingHeaderObj.shif_fft | |
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134 | self.dataOut.frequency = self.frequency | |
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135 | ||
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136 | def getBasicHeader(self): | |
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137 | self.dataOut.utctime = self.basicHeaderObj.utc + self.basicHeaderObj.miliSecond / \ | |
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138 | 1000. + self.profileIndex * self.radarControllerHeaderObj.ippSeconds | |
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139 | ||
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140 | self.dataOut.flagDiscontinuousBlock = self.flagDiscontinuousBlock | |
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141 | self.dataOut.timeZone = self.basicHeaderObj.timeZone | |
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142 | self.dataOut.dstFlag = self.basicHeaderObj.dstFlag | |
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143 | self.dataOut.errorCount = self.basicHeaderObj.errorCount | |
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144 | self.dataOut.useLocalTime = self.basicHeaderObj.useLocalTime | |
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145 | self.dataOut.ippSeconds = self.radarControllerHeaderObj.ippSeconds / self.nTxs | |
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146 | ||
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147 | def set_RCH(self, expType=2, nTx=1,ipp=None, txA=0, txB=0, | |
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148 | nWindows=None, nHeights=None, firstHeight=None, deltaHeight=None, | |
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149 | numTaus=0, line6Function=0, line5Function=0, fClock=None, | |
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150 | prePulseBefore=0, prePulseAfter=0, | |
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151 | codeType=0, nCode=0, nBaud=0, code=None, | |
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152 | flip1=0, flip2=0): | |
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153 | self.radarControllerHeaderObj.expType = expType | |
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154 | self.radarControllerHeaderObj.nTx = nTx | |
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155 | self.radarControllerHeaderObj.ipp = float(ipp) | |
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156 | self.radarControllerHeaderObj.txA = float(txA) | |
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157 | self.radarControllerHeaderObj.txB = float(txB) | |
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158 | self.radarControllerHeaderObj.rangeIPP = ipp | |
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159 | self.radarControllerHeaderObj.rangeTxA = txA | |
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160 | self.radarControllerHeaderObj.rangeTxB = txB | |
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161 | ||
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162 | self.radarControllerHeaderObj.nHeights = int(nHeights) | |
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163 | self.radarControllerHeaderObj.firstHeight = numpy.array([firstHeight]) | |
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164 | self.radarControllerHeaderObj.deltaHeight = numpy.array([deltaHeight]) | |
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165 | self.radarControllerHeaderObj.samplesWin = numpy.array([nHeights]) | |
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166 | ||
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167 | ||
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168 | self.radarControllerHeaderObj.nWindows = nWindows | |
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169 | self.radarControllerHeaderObj.numTaus = numTaus | |
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170 | self.radarControllerHeaderObj.codeType = codeType | |
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171 | self.radarControllerHeaderObj.line6Function = line6Function | |
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172 | self.radarControllerHeaderObj.line5Function = line5Function | |
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173 | self.radarControllerHeaderObj.fclock = fClock | |
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174 | self.radarControllerHeaderObj.prePulseBefore= prePulseBefore | |
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175 | self.radarControllerHeaderObj.prePulseAfter = prePulseAfter | |
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176 | ||
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177 | self.radarControllerHeaderObj.nCode = nCode | |
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178 | self.radarControllerHeaderObj.nBaud = nBaud | |
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179 | self.radarControllerHeaderObj.code = code | |
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180 | self.radarControllerHeaderObj.flip1 = flip1 | |
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181 | self.radarControllerHeaderObj.flip2 = flip2 | |
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182 | ||
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183 | self.radarControllerHeaderObj.code_size = int(numpy.ceil(nBaud / 32.)) * nCode * 4 | |
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184 | ||
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185 | if fClock is None and deltaHeight is not None: | |
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186 | self.fClock = 0.15 / (deltaHeight * 1e-6) | |
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187 | ||
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188 | def set_PH(self, dtype=0, blockSize=0, profilesPerBlock=0, | |
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189 | dataBlocksPerFile=0, nWindows=0, processFlags=0, nCohInt=0, | |
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190 | nIncohInt=0, totalSpectra=0, nHeights=0, firstHeight=0, | |
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191 | deltaHeight=0, samplesWin=0, spectraComb=0, nCode=0, | |
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192 | code=0, nBaud=None, shif_fft=False, flag_dc=False, | |
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193 | flag_cspc=False, flag_decode=False, flag_deflip=False): | |
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194 | ||
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195 | self.processingHeaderObj.profilesPerBlock = profilesPerBlock | |
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196 | self.processingHeaderObj.dataBlocksPerFile = dataBlocksPerFile | |
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197 | self.processingHeaderObj.nWindows = nWindows | |
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198 | self.processingHeaderObj.nCohInt = nCohInt | |
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199 | self.processingHeaderObj.nIncohInt = nIncohInt | |
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200 | self.processingHeaderObj.totalSpectra = totalSpectra | |
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201 | self.processingHeaderObj.nHeights = int(nHeights) | |
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202 | self.processingHeaderObj.firstHeight = firstHeight | |
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203 | self.processingHeaderObj.deltaHeight = deltaHeight | |
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204 | self.processingHeaderObj.samplesWin = nHeights | |
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205 | ||
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206 | def set_BH(self, utc = 0, miliSecond = 0, timeZone = 0): | |
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207 | self.basicHeaderObj.utc = utc | |
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208 | self.basicHeaderObj.miliSecond = miliSecond | |
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209 | self.basicHeaderObj.timeZone = timeZone | |
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210 | ||
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211 | def set_SH(self, nSamples=0, nProfiles=0, nChannels=0, adcResolution=14, pciDioBusWidth=0): | |
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212 | self.systemHeaderObj.nSamples = nSamples | |
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213 | self.systemHeaderObj.nProfiles = nProfiles | |
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214 | self.systemHeaderObj.nChannels = nChannels | |
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215 | self.systemHeaderObj.adcResolution = adcResolution | |
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216 | self.systemHeaderObj.pciDioBusWidth = pciDioBusWidth | |
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217 | ||
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218 | def init_acquisition(self): | |
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219 | ||
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220 | if self.nFFTPoints != 0: | |
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221 | self.incIntFactor = m_nProfilesperBlock/self.nFFTPoints | |
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222 | if (self.FixPP_IncInt > self.incIntFactor): | |
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223 | self.incIntFactor = self.FixPP_IncInt/ self.incIntFactor | |
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224 | elif(self.FixPP_IncInt< self.incIntFactor): | |
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225 | print("False alert...") | |
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226 | ||
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227 | ProfilesperBlock = self.processingHeaderObj.profilesPerBlock | |
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228 | ||
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229 | self.timeperblock =int(((self.FixRCP_IPP | |
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230 | *ProfilesperBlock | |
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231 | *self.FixPP_CohInt | |
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232 | *self.incIntFactor) | |
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233 | /150.0) | |
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234 | *0.9 | |
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235 | +0.5) | |
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236 | # para cada canal | |
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237 | self.profiles = ProfilesperBlock*self.FixPP_CohInt | |
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238 | self.profiles = ProfilesperBlock | |
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239 | self.Reference = int((self.Tau_0-self.AcqH0_0)/(self.AcqDH_0)+0.5) | |
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240 | self.BaudWidth = int((self.FixRCP_TXA/self.AcqDH_0)/self.Bauds + 0.5 ) | |
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241 | ||
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242 | if (self.BaudWidth==0): | |
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243 | self.BaudWidth=1 | |
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244 | ||
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245 | def init_pulse(self,Num_Codes=Num_Codes,Bauds=Bauds,BaudWidth=BaudWidth,Dyn_snCode=Dyn_snCode): | |
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246 | ||
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247 | Num_Codes = Num_Codes | |
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248 | Bauds = Bauds | |
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249 | BaudWidth = BaudWidth | |
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250 | Dyn_snCode = Dyn_snCode | |
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251 | ||
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252 | if Dyn_snCode: | |
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253 | print("EXISTE") | |
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254 | else: | |
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255 | print("No existe") | |
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256 | ||
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257 | if Dyn_snCode: # if Bauds: | |
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258 | pulses = list(range(0,Num_Codes)) | |
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259 | num_codes = Num_Codes | |
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260 | for i in range(num_codes): | |
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261 | pulse_size = Bauds*BaudWidth | |
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262 | pulses[i] = numpy.zeros(pulse_size) | |
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263 | for j in range(Bauds): | |
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264 | for k in range(BaudWidth): | |
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265 | pulses[i][j*BaudWidth+k] = int(Dyn_snCode[i][j]*600) | |
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266 | else: | |
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267 | print("sin code") | |
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268 | pulses = list(range(1)) | |
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269 | if self.AcqDH_0>0.149: | |
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270 | pulse_size = int(self.FixRCP_TXB/0.15+0.5) | |
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271 | else: | |
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272 | pulse_size = int((self.FixRCP_TXB/self.AcqDH_0)+0.5) #0.0375 | |
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273 | pulses[0] = numpy.ones(pulse_size) | |
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274 | pulses = 600*pulses[0] | |
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275 | ||
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276 | return pulses,pulse_size | |
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277 | ||
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278 | def jro_GenerateBlockOfData(self,Samples=Samples,DC_level= DC_level,stdev=stdev, | |
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279 | Reference= Reference,pulses= pulses, | |
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280 | Num_Codes= Num_Codes,pulse_size=pulse_size, | |
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281 | prof_gen= prof_gen,H0 = H0,DH0=DH0, | |
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282 | Adoppler=Adoppler,Fdoppler= Fdoppler,Hdoppler=Hdoppler): | |
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283 | Samples = Samples | |
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284 | DC_level = DC_level | |
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285 | stdev = stdev | |
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286 | m_nR = Reference | |
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287 | pulses = pulses | |
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288 | num_codes = Num_Codes | |
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289 | ps = pulse_size | |
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290 | prof_gen = prof_gen | |
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291 | channels = self.channels | |
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292 | H0 = H0 | |
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293 | DH0 = DH0 | |
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294 | ippSec = self.radarControllerHeaderObj.ippSeconds | |
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295 | Fdoppler = self.Fdoppler | |
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296 | Hdoppler = self.Hdoppler | |
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297 | Adoppler = self.Adoppler | |
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298 | ||
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299 | self.datablock = numpy.zeros([channels,prof_gen,Samples],dtype= numpy.complex64) | |
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300 | for i in range(channels): | |
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301 | for k in range(prof_gen): | |
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302 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·NOISEΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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303 | Noise_r = numpy.random.normal(DC_level,stdev,Samples) | |
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304 | Noise_i = numpy.random.normal(DC_level,stdev,Samples) | |
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305 | Noise = numpy.zeros(Samples,dtype=complex) | |
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306 | Noise.real = Noise_r | |
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307 | Noise.imag = Noise_i | |
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308 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·PULSOSΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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309 | Pulso = numpy.zeros(pulse_size,dtype=complex) | |
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310 | Pulso.real = pulses[k%num_codes] | |
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311 | Pulso.imag = pulses[k%num_codes] | |
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312 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· PULSES+NOISEΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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313 | InBuffer = numpy.zeros(Samples,dtype=complex) | |
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314 | InBuffer[m_nR:m_nR+ps] = Pulso | |
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315 | InBuffer = InBuffer+Noise | |
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316 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· ANGLE Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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317 | InBuffer.real[m_nR:m_nR+ps] = InBuffer.real[m_nR:m_nR+ps]*(math.cos( self.fAngle)*5) | |
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318 | InBuffer.imag[m_nR:m_nR+ps] = InBuffer.imag[m_nR:m_nR+ps]*(math.sin( self.fAngle)*5) | |
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319 | InBuffer=InBuffer | |
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320 | self.datablock[i][k]= InBuffer | |
|
|
321 | #plot_cts(InBuffer,H0=H0,DH0=DH0) | |
|
|
322 | #wave_fft(x=InBuffer,plot_show=True) | |
|
|
323 | #time.sleep(1) | |
|
|
324 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·DOPPLER SIGNAL............................................... | |
|
|
325 | time_vec = numpy.linspace(0,(prof_gen-1)*ippSec,int(prof_gen))+self.nReadBlocks*ippSec*prof_gen+(self.nReadFiles-1)*ippSec*prof_gen | |
|
|
326 | fd = Fdoppler #+(600.0/120)*self.nReadBlocks | |
|
|
327 | d_signal = Adoppler*numpy.array(numpy.exp(1.0j*2.0*math.pi*fd*time_vec),dtype=numpy.complex64) | |
|
|
328 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· DATABLOCK + DOPPLERΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·........................... | |
|
|
329 | HD=int(Hdoppler/self.AcqDH_0) | |
|
|
330 | for i in range(12): | |
|
|
331 | self.datablock[:,:,HD+i]=self.datablock[:,:,HD+i]+ d_signal # RESULT | |
|
|
332 | ''' | |
|
|
333 | a= numpy.zeros(10) | |
|
|
334 | for i in range(10): | |
|
|
335 | a[i]=i+self.nReadBlocks+20 | |
|
|
336 | for i in a: | |
|
|
337 | self.datablock[0,:,int(i)]=self.datablock[0,:,int(i)]+ d_signal # RESULT | |
|
|
338 | ''' | |
|
|
339 | ||
|
|
340 | def readBlock(self): | |
|
|
341 | ||
|
|
342 | self.jro_GenerateBlockOfData(Samples= self.samples,DC_level=self.DC_level, | |
|
|
343 | stdev=self.stdev,Reference= self.Reference, | |
|
|
344 | pulses = self.pulses,Num_Codes=self.Num_Codes, | |
|
|
345 | pulse_size=self.pulse_size,prof_gen=self.profiles, | |
|
|
346 | H0=self.H0,DH0=self.DH0) | |
|
|
347 | ||
|
|
348 | self.profileIndex = 0 | |
|
|
349 | self.flagIsNewFile = 0 | |
|
|
350 | self.flagIsNewBlock = 1 | |
|
|
351 | self.nTotalBlocks += 1 | |
|
|
352 | self.nReadBlocks += 1 | |
|
|
353 | ||
|
|
354 | return 1 | |
|
|
355 | ||
|
|
356 | ||
|
|
357 | def getData(self): | |
|
|
358 | if self.flagNoMoreFiles: | |
|
|
359 | self.dataOut.flagNodata = True | |
|
|
360 | return 0 | |
|
|
361 | self.flagDiscontinuousBlock = 0 | |
|
|
362 | self.flagIsNewBlock = 0 | |
|
|
363 | if self.__hasNotDataInBuffer(): # aqui es verdad | |
|
|
364 | if not(self.readNextBlock()): # return 1 y por eso el if not salta a getBasic Header | |
|
|
365 | return 0 | |
|
|
366 | self.getFirstHeader() # atributo | |
|
|
367 | ||
|
|
368 | if not self.getByBlock: | |
|
|
369 | self.dataOut.flagDataAsBlock = False | |
|
|
370 | self.dataOut.data = self.datablock[:, self.profileIndex, :] | |
|
|
371 | self.dataOut.profileIndex = self.profileIndex | |
|
|
372 | self.profileIndex += 1 | |
|
|
373 | else: | |
|
|
374 | pass | |
|
|
375 | self.dataOut.flagNoData = False | |
|
|
376 | self.getBasicHeader() | |
|
|
377 | self.dataOut.realtime = self.online | |
|
|
378 | return self.dataOut.data | |
|
|
379 | ||
|
|
380 | ||
|
|
381 | def setup(self,frequency=49.92e6,incIntFactor= 1, nFFTPoints = 0, FixPP_IncInt=1,FixRCP_IPP=1000, | |
|
|
382 | FixPP_CohInt= 1,Tau_0= 250,AcqH0_0 = 70 ,AcqDH_0=1.25, Bauds= 32, | |
|
|
383 | FixRCP_TXA = 40, FixRCP_TXB = 50, fAngle = 2.0*math.pi*(1/16),DC_level= 50, | |
|
|
384 | stdev= 8,Num_Codes = 1 , Dyn_snCode = None, samples=200, | |
|
|
385 | channels=2,Fdoppler=20,Hdoppler=36,Adoppler=500,nTotalReadFiles=10000, | |
|
|
386 | **kwargs): | |
|
|
387 | ||
|
|
388 | self.set_kwargs(**kwargs) | |
|
|
389 | self.nReadBlocks = 0 | |
|
|
390 | self.nReadFiles = 1 | |
|
|
391 | print('------------------- [Opening file: ] ------------------------------',self.nReadFiles) | |
|
|
392 | ||
|
|
393 | tmp = time.time() | |
|
|
394 | tmp_utc = int(tmp) | |
|
|
395 | tmp_milisecond = int((tmp-tmp_utc)*1000) | |
|
|
396 | print(" SETUP -basicHeaderObj.utc",datetime.datetime.utcfromtimestamp(tmp)) | |
|
|
397 | if Dyn_snCode is None: | |
|
|
398 | Num_Codes=1 | |
|
|
399 | Bauds =1 | |
|
|
400 | ||
|
|
401 | ||
|
|
402 | ||
|
|
403 | self.set_BH(utc= tmp_utc,miliSecond= tmp_milisecond,timeZone=300 ) | |
|
|
404 | ||
|
|
405 | self.set_RCH( expType=0, nTx=150,ipp=FixRCP_IPP, txA=FixRCP_TXA, txB= FixRCP_TXB, | |
|
|
406 | nWindows=1 , nHeights=samples, firstHeight=AcqH0_0, deltaHeight=AcqDH_0, | |
|
|
407 | numTaus=1, line6Function=0, line5Function=0, fClock=None, | |
|
|
408 | prePulseBefore=0, prePulseAfter=0, | |
|
|
409 | codeType=14, nCode=Num_Codes, nBaud=32, code=Dyn_snCode, | |
|
|
410 | flip1=0, flip2=0) | |
|
|
411 | ||
|
|
412 | self.set_PH(dtype=0, blockSize=0, profilesPerBlock=300, | |
|
|
413 | dataBlocksPerFile=120, nWindows=1, processFlags=0, nCohInt=1, | |
|
|
414 | nIncohInt=1, totalSpectra=0, nHeights=samples, firstHeight=AcqH0_0, | |
|
|
415 | deltaHeight=AcqDH_0, samplesWin=samples, spectraComb=0, nCode=0, | |
|
|
416 | code=0, nBaud=None, shif_fft=False, flag_dc=False, | |
|
|
417 | flag_cspc=False, flag_decode=False, flag_deflip=False) | |
|
|
418 | ||
|
|
419 | self.set_SH(nSamples=samples, nProfiles=300, nChannels=channels) | |
|
|
420 | ||
|
|
421 | ||
|
|
422 | self.frequency = frequency | |
|
|
423 | self.incIntFactor = incIntFactor | |
|
|
424 | self.nFFTPoints = nFFTPoints | |
|
|
425 | self.FixPP_IncInt = FixPP_IncInt | |
|
|
426 | self.FixRCP_IPP = FixRCP_IPP | |
|
|
427 | self.FixPP_CohInt = FixPP_CohInt | |
|
|
428 | self.Tau_0 = Tau_0 | |
|
|
429 | self.AcqH0_0 = AcqH0_0 | |
|
|
430 | self.H0 = AcqH0_0 | |
|
|
431 | self.AcqDH_0 = AcqDH_0 | |
|
|
432 | self.DH0 = AcqDH_0 | |
|
|
433 | self.Bauds = Bauds | |
|
|
434 | self.FixRCP_TXA = FixRCP_TXA | |
|
|
435 | self.FixRCP_TXB = FixRCP_TXB | |
|
|
436 | self.fAngle = fAngle | |
|
|
437 | self.DC_level = DC_level | |
|
|
438 | self.stdev = stdev | |
|
|
439 | self.Num_Codes = Num_Codes | |
|
|
440 | self.Dyn_snCode = Dyn_snCode | |
|
|
441 | self.samples = samples | |
|
|
442 | self.channels = channels | |
|
|
443 | self.profiles = None | |
|
|
444 | self.m_nReference = None | |
|
|
445 | self.Baudwidth = None | |
|
|
446 | self.Fdoppler = Fdoppler | |
|
|
447 | self.Hdoppler = Hdoppler | |
|
|
448 | self.Adoppler = Adoppler | |
|
|
449 | self.nTotalReadFiles = int(nTotalReadFiles) | |
|
|
450 | ||
|
|
451 | print("IPP ", self.FixRCP_IPP) | |
|
|
452 | print("Tau_0 ",self.Tau_0) | |
|
|
453 | print("AcqH0_0",self.AcqH0_0) | |
|
|
454 | print("samples,window ",self.samples) | |
|
|
455 | print("AcqDH_0",AcqDH_0) | |
|
|
456 | print("FixRCP_TXA",self.FixRCP_TXA) | |
|
|
457 | print("FixRCP_TXB",self.FixRCP_TXB) | |
|
|
458 | print("Dyn_snCode",Dyn_snCode) | |
|
|
459 | print("Fdoppler", Fdoppler) | |
|
|
460 | print("Hdoppler",Hdoppler) | |
|
|
461 | print("Vdopplermax",Fdoppler*(3.0e8/self.frequency)/2.0) | |
|
|
462 | print("nTotalReadFiles", nTotalReadFiles) | |
|
|
463 | ||
|
|
464 | self.init_acquisition() | |
|
|
465 | self.pulses,self.pulse_size=self.init_pulse(Num_Codes=self.Num_Codes,Bauds=self.Bauds,BaudWidth=self.BaudWidth,Dyn_snCode=Dyn_snCode) | |
|
|
466 | print(" [ END ] - SETUP metodo") | |
|
|
467 | return | |
|
|
468 | ||
|
|
469 | def run(self,**kwargs): # metodo propio | |
|
|
470 | if not(self.isConfig): | |
|
|
471 | self.setup(**kwargs) | |
|
|
472 | self.isConfig = True | |
|
|
473 | self.getData() | |
| @@ -1,1386 +1,1393 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | |
|
|
3 | 3 | $Author: murco $ |
|
|
4 | 4 | $Id: JROData.py 173 2012-11-20 15:06:21Z murco $ |
|
|
5 | 5 | ''' |
|
|
6 | 6 | |
|
|
7 | 7 | import copy |
|
|
8 | 8 | import numpy |
|
|
9 | 9 | import datetime |
|
|
10 | 10 | import json |
|
|
11 | 11 | |
|
|
12 | 12 | import schainpy.admin |
|
|
13 | 13 | from schainpy.utils import log |
|
|
14 | 14 | from .jroheaderIO import SystemHeader, RadarControllerHeader |
|
|
15 | 15 | from schainpy.model.data import _noise |
|
|
16 | 16 | |
|
|
17 | 17 | |
|
|
18 | 18 | def getNumpyDtype(dataTypeCode): |
|
|
19 | 19 | |
|
|
20 | 20 | if dataTypeCode == 0: |
|
|
21 | 21 | numpyDtype = numpy.dtype([('real', '<i1'), ('imag', '<i1')]) |
|
|
22 | 22 | elif dataTypeCode == 1: |
|
|
23 | 23 | numpyDtype = numpy.dtype([('real', '<i2'), ('imag', '<i2')]) |
|
|
24 | 24 | elif dataTypeCode == 2: |
|
|
25 | 25 | numpyDtype = numpy.dtype([('real', '<i4'), ('imag', '<i4')]) |
|
|
26 | 26 | elif dataTypeCode == 3: |
|
|
27 | 27 | numpyDtype = numpy.dtype([('real', '<i8'), ('imag', '<i8')]) |
|
|
28 | 28 | elif dataTypeCode == 4: |
|
|
29 | 29 | numpyDtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) |
|
|
30 | 30 | elif dataTypeCode == 5: |
|
|
31 | 31 | numpyDtype = numpy.dtype([('real', '<f8'), ('imag', '<f8')]) |
|
|
32 | 32 | else: |
|
|
33 | 33 | raise ValueError('dataTypeCode was not defined') |
|
|
34 | 34 | |
|
|
35 | 35 | return numpyDtype |
|
|
36 | 36 | |
|
|
37 | 37 | |
|
|
38 | 38 | def getDataTypeCode(numpyDtype): |
|
|
39 | 39 | |
|
|
40 | 40 | if numpyDtype == numpy.dtype([('real', '<i1'), ('imag', '<i1')]): |
|
|
41 | 41 | datatype = 0 |
|
|
42 | 42 | elif numpyDtype == numpy.dtype([('real', '<i2'), ('imag', '<i2')]): |
|
|
43 | 43 | datatype = 1 |
|
|
44 | 44 | elif numpyDtype == numpy.dtype([('real', '<i4'), ('imag', '<i4')]): |
|
|
45 | 45 | datatype = 2 |
|
|
46 | 46 | elif numpyDtype == numpy.dtype([('real', '<i8'), ('imag', '<i8')]): |
|
|
47 | 47 | datatype = 3 |
|
|
48 | 48 | elif numpyDtype == numpy.dtype([('real', '<f4'), ('imag', '<f4')]): |
|
|
49 | 49 | datatype = 4 |
|
|
50 | 50 | elif numpyDtype == numpy.dtype([('real', '<f8'), ('imag', '<f8')]): |
|
|
51 | 51 | datatype = 5 |
|
|
52 | 52 | else: |
|
|
53 | 53 | datatype = None |
|
|
54 | 54 | |
|
|
55 | 55 | return datatype |
|
|
56 | 56 | |
|
|
57 | 57 | |
|
|
58 | 58 | def hildebrand_sekhon(data, navg): |
|
|
59 | 59 | """ |
|
|
60 | 60 | This method is for the objective determination of the noise level in Doppler spectra. This |
|
|
61 | 61 | implementation technique is based on the fact that the standard deviation of the spectral |
|
|
62 | 62 | densities is equal to the mean spectral density for white Gaussian noise |
|
|
63 | 63 | |
|
|
64 | 64 | Inputs: |
|
|
65 | 65 | Data : heights |
|
|
66 | 66 | navg : numbers of averages |
|
|
67 | 67 | |
|
|
68 | 68 | Return: |
|
|
69 | 69 | mean : noise's level |
|
|
70 | 70 | """ |
|
|
71 | 71 | |
|
|
72 | 72 | sortdata = numpy.sort(data, axis=None) |
|
|
73 | 73 | ''' |
|
|
74 | 74 | lenOfData = len(sortdata) |
|
|
75 | 75 | nums_min = lenOfData*0.2 |
|
|
76 | 76 | |
|
|
77 | 77 | if nums_min <= 5: |
|
|
78 | 78 | |
|
|
79 | 79 | nums_min = 5 |
|
|
80 | 80 | |
|
|
81 | 81 | sump = 0. |
|
|
82 | 82 | sumq = 0. |
|
|
83 | 83 | |
|
|
84 | 84 | j = 0 |
|
|
85 | 85 | cont = 1 |
|
|
86 | 86 | |
|
|
87 | 87 | while((cont == 1)and(j < lenOfData)): |
|
|
88 | 88 | |
|
|
89 | 89 | sump += sortdata[j] |
|
|
90 | 90 | sumq += sortdata[j]**2 |
|
|
91 | 91 | |
|
|
92 | 92 | if j > nums_min: |
|
|
93 | 93 | rtest = float(j)/(j-1) + 1.0/navg |
|
|
94 | 94 | if ((sumq*j) > (rtest*sump**2)): |
|
|
95 | 95 | j = j - 1 |
|
|
96 | 96 | sump = sump - sortdata[j] |
|
|
97 | 97 | sumq = sumq - sortdata[j]**2 |
|
|
98 | 98 | cont = 0 |
|
|
99 | 99 | |
|
|
100 | 100 | j += 1 |
|
|
101 | 101 | |
|
|
102 | 102 | lnoise = sump / j |
|
|
103 | 103 | ''' |
|
|
104 | 104 | return _noise.hildebrand_sekhon(sortdata, navg) |
|
|
105 | 105 | |
|
|
106 | 106 | |
|
|
107 | 107 | class Beam: |
|
|
108 | 108 | |
|
|
109 | 109 | def __init__(self): |
|
|
110 | 110 | self.codeList = [] |
|
|
111 | 111 | self.azimuthList = [] |
|
|
112 | 112 | self.zenithList = [] |
|
|
113 | 113 | |
|
|
114 | 114 | |
|
|
115 | 115 | class GenericData(object): |
|
|
116 | 116 | |
|
|
117 | 117 | flagNoData = True |
|
|
118 | 118 | |
|
|
119 | 119 | def copy(self, inputObj=None): |
|
|
120 | 120 | |
|
|
121 | 121 | if inputObj == None: |
|
|
122 | 122 | return copy.deepcopy(self) |
|
|
123 | 123 | |
|
|
124 | 124 | for key in list(inputObj.__dict__.keys()): |
|
|
125 | 125 | |
|
|
126 | 126 | attribute = inputObj.__dict__[key] |
|
|
127 | 127 | |
|
|
128 | 128 | # If this attribute is a tuple or list |
|
|
129 | 129 | if type(inputObj.__dict__[key]) in (tuple, list): |
|
|
130 | 130 | self.__dict__[key] = attribute[:] |
|
|
131 | 131 | continue |
|
|
132 | 132 | |
|
|
133 | 133 | # If this attribute is another object or instance |
|
|
134 | 134 | if hasattr(attribute, '__dict__'): |
|
|
135 | 135 | self.__dict__[key] = attribute.copy() |
|
|
136 | 136 | continue |
|
|
137 | 137 | |
|
|
138 | 138 | self.__dict__[key] = inputObj.__dict__[key] |
|
|
139 | 139 | |
|
|
140 | 140 | def deepcopy(self): |
|
|
141 | 141 | |
|
|
142 | 142 | return copy.deepcopy(self) |
|
|
143 | 143 | |
|
|
144 | 144 | def isEmpty(self): |
|
|
145 | 145 | |
|
|
146 | 146 | return self.flagNoData |
|
|
147 | 147 | |
|
|
148 | 148 | def isReady(self): |
|
|
149 | 149 | |
|
|
150 | 150 | return not self.flagNoData |
|
|
151 | 151 | |
|
|
152 | 152 | |
|
|
153 | 153 | class JROData(GenericData): |
|
|
154 | 154 | |
|
|
155 | 155 | # m_BasicHeader = BasicHeader() |
|
|
156 | 156 | # m_ProcessingHeader = ProcessingHeader() |
|
|
157 | 157 | |
|
|
158 | 158 | systemHeaderObj = SystemHeader() |
|
|
159 | 159 | radarControllerHeaderObj = RadarControllerHeader() |
|
|
160 | 160 | # data = None |
|
|
161 | 161 | type = None |
|
|
162 | 162 | datatype = None # dtype but in string |
|
|
163 | 163 | # dtype = None |
|
|
164 | 164 | # nChannels = None |
|
|
165 | 165 | # nHeights = None |
|
|
166 | 166 | nProfiles = None |
|
|
167 | 167 | heightList = None |
|
|
168 | 168 | channelList = None |
|
|
169 | 169 | flagDiscontinuousBlock = False |
|
|
170 | 170 | useLocalTime = False |
|
|
171 | 171 | utctime = None |
|
|
172 | 172 | timeZone = None |
|
|
173 | 173 | dstFlag = None |
|
|
174 | 174 | errorCount = None |
|
|
175 | 175 | blocksize = None |
|
|
176 | 176 | # nCode = None |
|
|
177 | 177 | # nBaud = None |
|
|
178 | 178 | # code = None |
|
|
179 | 179 | flagDecodeData = False # asumo q la data no esta decodificada |
|
|
180 | 180 | flagDeflipData = False # asumo q la data no esta sin flip |
|
|
181 | 181 | flagShiftFFT = False |
|
|
182 | 182 | # ippSeconds = None |
|
|
183 | 183 | # timeInterval = None |
|
|
184 | 184 | nCohInt = None |
|
|
185 | 185 | # noise = None |
|
|
186 | 186 | windowOfFilter = 1 |
|
|
187 | 187 | # Speed of ligth |
|
|
188 | 188 | C = 3e8 |
|
|
189 | 189 | frequency = 49.92e6 |
|
|
190 | 190 | realtime = False |
|
|
191 | 191 | beacon_heiIndexList = None |
|
|
192 | 192 | last_block = None |
|
|
193 | 193 | blocknow = None |
|
|
194 | 194 | azimuth = None |
|
|
195 | 195 | zenith = None |
|
|
196 | 196 | beam = Beam() |
|
|
197 | 197 | profileIndex = None |
|
|
198 | 198 | error = None |
|
|
199 | 199 | data = None |
|
|
200 | 200 | nmodes = None |
|
|
201 | 201 | |
|
|
202 | 202 | def __str__(self): |
|
|
203 | 203 | |
|
|
204 | 204 | return '{} - {}'.format(self.type, self.getDatatime()) |
|
|
205 | 205 | |
|
|
206 | 206 | def getNoise(self): |
|
|
207 | 207 | |
|
|
208 | 208 | raise NotImplementedError |
|
|
209 | 209 | |
|
|
210 | 210 | def getNChannels(self): |
|
|
211 | 211 | |
|
|
212 | 212 | return len(self.channelList) |
|
|
213 | 213 | |
|
|
214 | 214 | def getChannelIndexList(self): |
|
|
215 | 215 | |
|
|
216 | 216 | return list(range(self.nChannels)) |
|
|
217 | 217 | |
|
|
218 | 218 | def getNHeights(self): |
|
|
219 | 219 | |
|
|
220 | 220 | return len(self.heightList) |
|
|
221 | 221 | |
|
|
222 | 222 | def getHeiRange(self, extrapoints=0): |
|
|
223 | 223 | |
|
|
224 | 224 | heis = self.heightList |
|
|
225 | 225 | # deltah = self.heightList[1] - self.heightList[0] |
|
|
226 | 226 | # |
|
|
227 | 227 | # heis.append(self.heightList[-1]) |
|
|
228 | 228 | |
|
|
229 | 229 | return heis |
|
|
230 | 230 | |
|
|
231 | 231 | def getDeltaH(self): |
|
|
232 | 232 | |
|
|
233 | 233 | delta = self.heightList[1] - self.heightList[0] |
|
|
234 | 234 | |
|
|
235 | 235 | return delta |
|
|
236 | 236 | |
|
|
237 | 237 | def getltctime(self): |
|
|
238 | 238 | |
|
|
239 | 239 | if self.useLocalTime: |
|
|
240 | 240 | return self.utctime - self.timeZone * 60 |
|
|
241 | 241 | |
|
|
242 | 242 | return self.utctime |
|
|
243 | 243 | |
|
|
244 | 244 | def getDatatime(self): |
|
|
245 | 245 | |
|
|
246 | 246 | datatimeValue = datetime.datetime.utcfromtimestamp(self.ltctime) |
|
|
247 | 247 | return datatimeValue |
|
|
248 | 248 | |
|
|
249 | 249 | def getTimeRange(self): |
|
|
250 | 250 | |
|
|
251 | 251 | datatime = [] |
|
|
252 | 252 | |
|
|
253 | 253 | datatime.append(self.ltctime) |
|
|
254 | 254 | datatime.append(self.ltctime + self.timeInterval + 1) |
|
|
255 | 255 | |
|
|
256 | 256 | datatime = numpy.array(datatime) |
|
|
257 | 257 | |
|
|
258 | 258 | return datatime |
|
|
259 | 259 | |
|
|
260 | 260 | def getFmaxTimeResponse(self): |
|
|
261 | 261 | |
|
|
262 | 262 | period = (10**-6) * self.getDeltaH() / (0.15) |
|
|
263 | 263 | |
|
|
264 | 264 | PRF = 1. / (period * self.nCohInt) |
|
|
265 | 265 | |
|
|
266 | 266 | fmax = PRF |
|
|
267 | 267 | |
|
|
268 | 268 | return fmax |
|
|
269 | 269 | |
|
|
270 | 270 | def getFmax(self): |
|
|
271 | 271 | PRF = 1. / (self.ippSeconds * self.nCohInt) |
|
|
272 | 272 | |
|
|
273 | 273 | fmax = PRF |
|
|
274 | 274 | return fmax |
|
|
275 | 275 | |
|
|
276 | 276 | def getVmax(self): |
|
|
277 | 277 | |
|
|
278 | 278 | _lambda = self.C / self.frequency |
|
|
279 | 279 | |
|
|
280 | 280 | vmax = self.getFmax() * _lambda / 2 |
|
|
281 | 281 | |
|
|
282 | 282 | return vmax |
|
|
283 | 283 | |
|
|
284 | 284 | def get_ippSeconds(self): |
|
|
285 | 285 | ''' |
|
|
286 | 286 | ''' |
|
|
287 | 287 | return self.radarControllerHeaderObj.ippSeconds |
|
|
288 | 288 | |
|
|
289 | 289 | def set_ippSeconds(self, ippSeconds): |
|
|
290 | 290 | ''' |
|
|
291 | 291 | ''' |
|
|
292 | 292 | |
|
|
293 | 293 | self.radarControllerHeaderObj.ippSeconds = ippSeconds |
|
|
294 | 294 | |
|
|
295 | 295 | return |
|
|
296 | 296 | |
|
|
297 | 297 | def get_dtype(self): |
|
|
298 | 298 | ''' |
|
|
299 | 299 | ''' |
|
|
300 | 300 | return getNumpyDtype(self.datatype) |
|
|
301 | 301 | |
|
|
302 | 302 | def set_dtype(self, numpyDtype): |
|
|
303 | 303 | ''' |
|
|
304 | 304 | ''' |
|
|
305 | 305 | |
|
|
306 | 306 | self.datatype = getDataTypeCode(numpyDtype) |
|
|
307 | 307 | |
|
|
308 | 308 | def get_code(self): |
|
|
309 | 309 | ''' |
|
|
310 | 310 | ''' |
|
|
311 | 311 | return self.radarControllerHeaderObj.code |
|
|
312 | 312 | |
|
|
313 | 313 | def set_code(self, code): |
|
|
314 | 314 | ''' |
|
|
315 | 315 | ''' |
|
|
316 | 316 | self.radarControllerHeaderObj.code = code |
|
|
317 | 317 | |
|
|
318 | 318 | return |
|
|
319 | 319 | |
|
|
320 | 320 | def get_ncode(self): |
|
|
321 | 321 | ''' |
|
|
322 | 322 | ''' |
|
|
323 | 323 | return self.radarControllerHeaderObj.nCode |
|
|
324 | 324 | |
|
|
325 | 325 | def set_ncode(self, nCode): |
|
|
326 | 326 | ''' |
|
|
327 | 327 | ''' |
|
|
328 | 328 | self.radarControllerHeaderObj.nCode = nCode |
|
|
329 | 329 | |
|
|
330 | 330 | return |
|
|
331 | 331 | |
|
|
332 | 332 | def get_nbaud(self): |
|
|
333 | 333 | ''' |
|
|
334 | 334 | ''' |
|
|
335 | 335 | return self.radarControllerHeaderObj.nBaud |
|
|
336 | 336 | |
|
|
337 | 337 | def set_nbaud(self, nBaud): |
|
|
338 | 338 | ''' |
|
|
339 | 339 | ''' |
|
|
340 | 340 | self.radarControllerHeaderObj.nBaud = nBaud |
|
|
341 | 341 | |
|
|
342 | 342 | return |
|
|
343 | 343 | |
|
|
344 | 344 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
|
|
345 | 345 | channelIndexList = property( |
|
|
346 | 346 | getChannelIndexList, "I'm the 'channelIndexList' property.") |
|
|
347 | 347 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
|
|
348 | 348 | #noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
349 | 349 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
|
350 | 350 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
|
351 | 351 | ippSeconds = property(get_ippSeconds, set_ippSeconds) |
|
|
352 | 352 | dtype = property(get_dtype, set_dtype) |
|
|
353 | 353 | # timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
354 | 354 | code = property(get_code, set_code) |
|
|
355 | 355 | nCode = property(get_ncode, set_ncode) |
|
|
356 | 356 | nBaud = property(get_nbaud, set_nbaud) |
|
|
357 | 357 | |
|
|
358 | 358 | |
|
|
359 | 359 | class Voltage(JROData): |
|
|
360 | 360 | |
|
|
361 | 361 | # data es un numpy array de 2 dmensiones (canales, alturas) |
|
|
362 | 362 | data = None |
|
|
363 | ||
|
|
363 | data_intensity = None | |
|
|
364 | data_velocity = None | |
|
|
364 | 365 | def __init__(self): |
|
|
365 | 366 | ''' |
|
|
366 | 367 | Constructor |
|
|
367 | 368 | ''' |
|
|
368 | 369 | |
|
|
369 | 370 | self.useLocalTime = True |
|
|
370 | 371 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
371 | 372 | self.systemHeaderObj = SystemHeader() |
|
|
372 | 373 | self.type = "Voltage" |
|
|
373 | 374 | self.data = None |
|
|
374 | 375 | # self.dtype = None |
|
|
375 | 376 | # self.nChannels = 0 |
|
|
376 | 377 | # self.nHeights = 0 |
|
|
377 | 378 | self.nProfiles = None |
|
|
378 | 379 | self.heightList = None |
|
|
379 | 380 | self.channelList = None |
|
|
380 | 381 | # self.channelIndexList = None |
|
|
381 | 382 | self.flagNoData = True |
|
|
382 | 383 | self.flagDiscontinuousBlock = False |
|
|
383 | 384 | self.utctime = None |
|
|
384 | 385 | self.timeZone = None |
|
|
385 | 386 | self.dstFlag = None |
|
|
386 | 387 | self.errorCount = None |
|
|
387 | 388 | self.nCohInt = None |
|
|
388 | 389 | self.blocksize = None |
|
|
389 | 390 | self.flagDecodeData = False # asumo q la data no esta decodificada |
|
|
390 | 391 | self.flagDeflipData = False # asumo q la data no esta sin flip |
|
|
391 | 392 | self.flagShiftFFT = False |
|
|
392 | 393 | self.flagDataAsBlock = False # Asumo que la data es leida perfil a perfil |
|
|
393 | 394 | self.profileIndex = 0 |
|
|
394 | 395 | |
|
|
395 | 396 | def getNoisebyHildebrand(self, channel=None): |
|
|
396 | 397 | """ |
|
|
397 | 398 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
|
|
398 | 399 | |
|
|
399 | 400 | Return: |
|
|
400 | 401 | noiselevel |
|
|
401 | 402 | """ |
|
|
402 | 403 | |
|
|
403 | 404 | if channel != None: |
|
|
404 | 405 | data = self.data[channel] |
|
|
405 | 406 | nChannels = 1 |
|
|
406 | 407 | else: |
|
|
407 | 408 | data = self.data |
|
|
408 | 409 | nChannels = self.nChannels |
|
|
409 | 410 | |
|
|
410 | 411 | noise = numpy.zeros(nChannels) |
|
|
411 | 412 | power = data * numpy.conjugate(data) |
|
|
412 | 413 | |
|
|
413 | 414 | for thisChannel in range(nChannels): |
|
|
414 | 415 | if nChannels == 1: |
|
|
415 | 416 | daux = power[:].real |
|
|
416 | 417 | else: |
|
|
417 | 418 | daux = power[thisChannel, :].real |
|
|
418 | 419 | noise[thisChannel] = hildebrand_sekhon(daux, self.nCohInt) |
|
|
419 | 420 | |
|
|
420 | 421 | return noise |
|
|
421 | 422 | |
|
|
422 | 423 | def getNoise(self, type=1, channel=None): |
|
|
423 | 424 | |
|
|
424 | 425 | if type == 1: |
|
|
425 | 426 | noise = self.getNoisebyHildebrand(channel) |
|
|
426 | 427 | |
|
|
427 | 428 | return noise |
|
|
428 | 429 | |
|
|
429 | 430 | def getPower(self, channel=None): |
|
|
430 | 431 | |
|
|
431 | 432 | if channel != None: |
|
|
432 | 433 | data = self.data[channel] |
|
|
433 | 434 | else: |
|
|
434 | 435 | data = self.data |
|
|
435 | 436 | |
|
|
436 | 437 | power = data * numpy.conjugate(data) |
|
|
437 | 438 | powerdB = 10 * numpy.log10(power.real) |
|
|
438 | 439 | powerdB = numpy.squeeze(powerdB) |
|
|
439 | 440 | |
|
|
440 | 441 | return powerdB |
|
|
441 | 442 | |
|
|
442 | 443 | def getTimeInterval(self): |
|
|
443 | 444 | |
|
|
444 | 445 | timeInterval = self.ippSeconds * self.nCohInt |
|
|
445 | 446 | |
|
|
446 | 447 | return timeInterval |
|
|
447 | 448 | |
|
|
448 | 449 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
449 | 450 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
450 | 451 | |
|
|
451 | 452 | |
|
|
452 | 453 | class Spectra(JROData): |
|
|
453 | 454 | |
|
|
454 | 455 | # data spc es un numpy array de 2 dmensiones (canales, perfiles, alturas) |
|
|
455 | 456 | data_spc = None |
|
|
456 | 457 | # data cspc es un numpy array de 2 dmensiones (canales, pares, alturas) |
|
|
457 | 458 | data_cspc = None |
|
|
458 | 459 | # data dc es un numpy array de 2 dmensiones (canales, alturas) |
|
|
459 | 460 | data_dc = None |
|
|
460 | 461 | # data power |
|
|
461 | 462 | data_pwr = None |
|
|
462 | 463 | nFFTPoints = None |
|
|
463 | 464 | # nPairs = None |
|
|
464 | 465 | pairsList = None |
|
|
465 | 466 | nIncohInt = None |
|
|
466 | 467 | wavelength = None # Necesario para cacular el rango de velocidad desde la frecuencia |
|
|
467 | 468 | nCohInt = None # se requiere para determinar el valor de timeInterval |
|
|
468 | 469 | ippFactor = None |
|
|
469 | 470 | profileIndex = 0 |
|
|
470 | 471 | plotting = "spectra" |
|
|
471 | 472 | |
|
|
472 | 473 | def __init__(self): |
|
|
473 | 474 | ''' |
|
|
474 | 475 | Constructor |
|
|
475 | 476 | ''' |
|
|
476 | 477 | |
|
|
477 | 478 | self.useLocalTime = True |
|
|
478 | 479 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
479 | 480 | self.systemHeaderObj = SystemHeader() |
|
|
480 | 481 | self.type = "Spectra" |
|
|
481 | 482 | # self.data = None |
|
|
482 | 483 | # self.dtype = None |
|
|
483 | 484 | # self.nChannels = 0 |
|
|
484 | 485 | # self.nHeights = 0 |
|
|
485 | 486 | self.nProfiles = None |
|
|
486 | 487 | self.heightList = None |
|
|
487 | 488 | self.channelList = None |
|
|
488 | 489 | # self.channelIndexList = None |
|
|
489 | 490 | self.pairsList = None |
|
|
490 | 491 | self.flagNoData = True |
|
|
491 | 492 | self.flagDiscontinuousBlock = False |
|
|
492 | 493 | self.utctime = None |
|
|
493 | 494 | self.nCohInt = None |
|
|
494 | 495 | self.nIncohInt = None |
|
|
495 | 496 | self.blocksize = None |
|
|
496 | 497 | self.nFFTPoints = None |
|
|
497 | 498 | self.wavelength = None |
|
|
498 | 499 | self.flagDecodeData = False # asumo q la data no esta decodificada |
|
|
499 | 500 | self.flagDeflipData = False # asumo q la data no esta sin flip |
|
|
500 | 501 | self.flagShiftFFT = False |
|
|
501 | 502 | self.ippFactor = 1 |
|
|
502 | 503 | #self.noise = None |
|
|
503 | 504 | self.beacon_heiIndexList = [] |
|
|
504 | 505 | self.noise_estimation = None |
|
|
505 | 506 | |
|
|
506 | 507 | def getNoisebyHildebrand(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): |
|
|
507 | 508 | """ |
|
|
508 | 509 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
|
|
509 | 510 | |
|
|
510 | 511 | Return: |
|
|
511 | 512 | noiselevel |
|
|
512 | 513 | """ |
|
|
513 | 514 | |
|
|
514 | 515 | noise = numpy.zeros(self.nChannels) |
|
|
515 | 516 | |
|
|
516 | 517 | for channel in range(self.nChannels): |
|
|
517 | 518 | daux = self.data_spc[channel, |
|
|
518 | 519 | xmin_index:xmax_index, ymin_index:ymax_index] |
|
|
519 | 520 | noise[channel] = hildebrand_sekhon(daux, self.nIncohInt) |
|
|
520 | 521 | |
|
|
521 | 522 | return noise |
|
|
522 | 523 | |
|
|
523 | 524 | def getNoise(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): |
|
|
524 | 525 | |
|
|
525 | 526 | if self.noise_estimation is not None: |
|
|
526 | 527 | # this was estimated by getNoise Operation defined in jroproc_spectra.py |
|
|
527 | 528 | return self.noise_estimation |
|
|
528 | 529 | else: |
|
|
529 | 530 | noise = self.getNoisebyHildebrand( |
|
|
530 | 531 | xmin_index, xmax_index, ymin_index, ymax_index) |
|
|
531 | 532 | return noise |
|
|
532 | 533 | |
|
|
533 | 534 | def getFreqRangeTimeResponse(self, extrapoints=0): |
|
|
534 | 535 | |
|
|
535 | 536 | deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints * self.ippFactor) |
|
|
536 | 537 | freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.) - deltafreq / 2 |
|
|
537 | 538 | |
|
|
538 | 539 | return freqrange |
|
|
539 | 540 | |
|
|
540 | 541 | def getAcfRange(self, extrapoints=0): |
|
|
541 | 542 | |
|
|
542 | 543 | deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor)) |
|
|
543 | 544 | freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2 |
|
|
544 | 545 | |
|
|
545 | 546 | return freqrange |
|
|
546 | 547 | |
|
|
547 | 548 | def getFreqRange(self, extrapoints=0): |
|
|
548 | 549 | |
|
|
549 | 550 | deltafreq = self.getFmax() / (self.nFFTPoints * self.ippFactor) |
|
|
550 | 551 | freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2 |
|
|
551 | 552 | |
|
|
552 | 553 | return freqrange |
|
|
553 | 554 | |
|
|
554 | 555 | def getVelRange(self, extrapoints=0): |
|
|
555 | 556 | |
|
|
556 | 557 | deltav = self.getVmax() / (self.nFFTPoints * self.ippFactor) |
|
|
557 | 558 | velrange = deltav * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.) |
|
|
558 | ||
|
|
559 | ||
|
|
559 | 560 | if self.nmodes: |
|
|
560 | 561 | return velrange/self.nmodes |
|
|
561 | 562 | else: |
|
|
562 | 563 | return velrange |
|
|
563 | 564 | |
|
|
564 | 565 | def getNPairs(self): |
|
|
565 | 566 | |
|
|
566 | 567 | return len(self.pairsList) |
|
|
567 | 568 | |
|
|
568 | 569 | def getPairsIndexList(self): |
|
|
569 | 570 | |
|
|
570 | 571 | return list(range(self.nPairs)) |
|
|
571 | 572 | |
|
|
572 | 573 | def getNormFactor(self): |
|
|
573 | 574 | |
|
|
574 | 575 | pwcode = 1 |
|
|
575 | 576 | |
|
|
576 | 577 | if self.flagDecodeData: |
|
|
577 | 578 | pwcode = numpy.sum(self.code[0]**2) |
|
|
578 | 579 | #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter |
|
|
579 | 580 | normFactor = self.nProfiles * self.nIncohInt * self.nCohInt * pwcode * self.windowOfFilter |
|
|
580 | 581 | |
|
|
581 | 582 | return normFactor |
|
|
582 | 583 | |
|
|
583 | 584 | def getFlagCspc(self): |
|
|
584 | 585 | |
|
|
585 | 586 | if self.data_cspc is None: |
|
|
586 | 587 | return True |
|
|
587 | 588 | |
|
|
588 | 589 | return False |
|
|
589 | 590 | |
|
|
590 | 591 | def getFlagDc(self): |
|
|
591 | 592 | |
|
|
592 | 593 | if self.data_dc is None: |
|
|
593 | 594 | return True |
|
|
594 | 595 | |
|
|
595 | 596 | return False |
|
|
596 | 597 | |
|
|
597 | 598 | def getTimeInterval(self): |
|
|
598 | 599 | |
|
|
599 | 600 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles * self.ippFactor |
|
|
600 | 601 | if self.nmodes: |
|
|
601 | 602 | return self.nmodes*timeInterval |
|
|
602 | 603 | else: |
|
|
603 | 604 | return timeInterval |
|
|
604 | 605 | |
|
|
605 | 606 | def getPower(self): |
|
|
606 | 607 | |
|
|
607 | 608 | factor = self.normFactor |
|
|
608 | 609 | z = self.data_spc / factor |
|
|
609 | 610 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
|
610 | 611 | avg = numpy.average(z, axis=1) |
|
|
611 | 612 | |
|
|
612 | 613 | return 10 * numpy.log10(avg) |
|
|
613 | 614 | |
|
|
614 | 615 | def getCoherence(self, pairsList=None, phase=False): |
|
|
615 | 616 | |
|
|
616 | 617 | z = [] |
|
|
617 | 618 | if pairsList is None: |
|
|
618 | 619 | pairsIndexList = self.pairsIndexList |
|
|
619 | 620 | else: |
|
|
620 | 621 | pairsIndexList = [] |
|
|
621 | 622 | for pair in pairsList: |
|
|
622 | 623 | if pair not in self.pairsList: |
|
|
623 | 624 | raise ValueError("Pair %s is not in dataOut.pairsList" % ( |
|
|
624 | 625 | pair)) |
|
|
625 | 626 | pairsIndexList.append(self.pairsList.index(pair)) |
|
|
626 | 627 | for i in range(len(pairsIndexList)): |
|
|
627 | 628 | pair = self.pairsList[pairsIndexList[i]] |
|
|
628 | 629 | ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0) |
|
|
629 | 630 | powa = numpy.average(self.data_spc[pair[0], :, :], axis=0) |
|
|
630 | 631 | powb = numpy.average(self.data_spc[pair[1], :, :], axis=0) |
|
|
631 | 632 | avgcoherenceComplex = ccf / numpy.sqrt(powa * powb) |
|
|
632 | 633 | if phase: |
|
|
633 | 634 | data = numpy.arctan2(avgcoherenceComplex.imag, |
|
|
634 | 635 | avgcoherenceComplex.real) * 180 / numpy.pi |
|
|
635 | 636 | else: |
|
|
636 | 637 | data = numpy.abs(avgcoherenceComplex) |
|
|
637 | 638 | |
|
|
638 | 639 | z.append(data) |
|
|
639 | 640 | |
|
|
640 | 641 | return numpy.array(z) |
|
|
641 | 642 | |
|
|
642 | 643 | def setValue(self, value): |
|
|
643 | 644 | |
|
|
644 | 645 | print("This property should not be initialized") |
|
|
645 | 646 | |
|
|
646 | 647 | return |
|
|
647 | 648 | |
|
|
648 | 649 | nPairs = property(getNPairs, setValue, "I'm the 'nPairs' property.") |
|
|
649 | 650 | pairsIndexList = property( |
|
|
650 | 651 | getPairsIndexList, setValue, "I'm the 'pairsIndexList' property.") |
|
|
651 | 652 | normFactor = property(getNormFactor, setValue, |
|
|
652 | 653 | "I'm the 'getNormFactor' property.") |
|
|
653 | 654 | flag_cspc = property(getFlagCspc, setValue) |
|
|
654 | 655 | flag_dc = property(getFlagDc, setValue) |
|
|
655 | 656 | noise = property(getNoise, setValue, "I'm the 'nHeights' property.") |
|
|
656 | 657 | timeInterval = property(getTimeInterval, setValue, |
|
|
657 | 658 | "I'm the 'timeInterval' property") |
|
|
658 | 659 | |
|
|
659 | 660 | |
|
|
660 | 661 | class SpectraHeis(Spectra): |
|
|
661 | 662 | |
|
|
662 | 663 | data_spc = None |
|
|
663 | 664 | data_cspc = None |
|
|
664 | 665 | data_dc = None |
|
|
665 | 666 | nFFTPoints = None |
|
|
666 | 667 | # nPairs = None |
|
|
667 | 668 | pairsList = None |
|
|
668 | 669 | nCohInt = None |
|
|
669 | 670 | nIncohInt = None |
|
|
670 | 671 | |
|
|
671 | 672 | def __init__(self): |
|
|
672 | 673 | |
|
|
673 | 674 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
674 | 675 | |
|
|
675 | 676 | self.systemHeaderObj = SystemHeader() |
|
|
676 | 677 | |
|
|
677 | 678 | self.type = "SpectraHeis" |
|
|
678 | 679 | |
|
|
679 | 680 | # self.dtype = None |
|
|
680 | 681 | |
|
|
681 | 682 | # self.nChannels = 0 |
|
|
682 | 683 | |
|
|
683 | 684 | # self.nHeights = 0 |
|
|
684 | 685 | |
|
|
685 | 686 | self.nProfiles = None |
|
|
686 | 687 | |
|
|
687 | 688 | self.heightList = None |
|
|
688 | 689 | |
|
|
689 | 690 | self.channelList = None |
|
|
690 | 691 | |
|
|
691 | 692 | # self.channelIndexList = None |
|
|
692 | 693 | |
|
|
693 | 694 | self.flagNoData = True |
|
|
694 | 695 | |
|
|
695 | 696 | self.flagDiscontinuousBlock = False |
|
|
696 | 697 | |
|
|
697 | 698 | # self.nPairs = 0 |
|
|
698 | 699 | |
|
|
699 | 700 | self.utctime = None |
|
|
700 | 701 | |
|
|
701 | 702 | self.blocksize = None |
|
|
702 | 703 | |
|
|
703 | 704 | self.profileIndex = 0 |
|
|
704 | 705 | |
|
|
705 | 706 | self.nCohInt = 1 |
|
|
706 | 707 | |
|
|
707 | 708 | self.nIncohInt = 1 |
|
|
708 | 709 | |
|
|
709 | 710 | def getNormFactor(self): |
|
|
710 | 711 | pwcode = 1 |
|
|
711 | 712 | if self.flagDecodeData: |
|
|
712 | 713 | pwcode = numpy.sum(self.code[0]**2) |
|
|
713 | 714 | |
|
|
714 | 715 | normFactor = self.nIncohInt * self.nCohInt * pwcode |
|
|
715 | 716 | |
|
|
716 | 717 | return normFactor |
|
|
717 | 718 | |
|
|
718 | 719 | def getTimeInterval(self): |
|
|
719 | 720 | |
|
|
720 | 721 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt |
|
|
721 | 722 | |
|
|
722 | 723 | return timeInterval |
|
|
723 | 724 | |
|
|
724 | 725 | normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.") |
|
|
725 | 726 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
726 | 727 | |
|
|
727 | 728 | |
|
|
728 | 729 | class Fits(JROData): |
|
|
729 | 730 | |
|
|
730 | 731 | heightList = None |
|
|
731 | 732 | channelList = None |
|
|
732 | 733 | flagNoData = True |
|
|
733 | 734 | flagDiscontinuousBlock = False |
|
|
734 | 735 | useLocalTime = False |
|
|
735 | 736 | utctime = None |
|
|
736 | 737 | timeZone = None |
|
|
737 | 738 | # ippSeconds = None |
|
|
738 | 739 | # timeInterval = None |
|
|
739 | 740 | nCohInt = None |
|
|
740 | 741 | nIncohInt = None |
|
|
741 | 742 | noise = None |
|
|
742 | 743 | windowOfFilter = 1 |
|
|
743 | 744 | # Speed of ligth |
|
|
744 | 745 | C = 3e8 |
|
|
745 | 746 | frequency = 49.92e6 |
|
|
746 | 747 | realtime = False |
|
|
747 | 748 | |
|
|
748 | 749 | def __init__(self): |
|
|
749 | 750 | |
|
|
750 | 751 | self.type = "Fits" |
|
|
751 | 752 | |
|
|
752 | 753 | self.nProfiles = None |
|
|
753 | 754 | |
|
|
754 | 755 | self.heightList = None |
|
|
755 | 756 | |
|
|
756 | 757 | self.channelList = None |
|
|
757 | 758 | |
|
|
758 | 759 | # self.channelIndexList = None |
|
|
759 | 760 | |
|
|
760 | 761 | self.flagNoData = True |
|
|
761 | 762 | |
|
|
762 | 763 | self.utctime = None |
|
|
763 | 764 | |
|
|
764 | 765 | self.nCohInt = 1 |
|
|
765 | 766 | |
|
|
766 | 767 | self.nIncohInt = 1 |
|
|
767 | 768 | |
|
|
768 | 769 | self.useLocalTime = True |
|
|
769 | 770 | |
|
|
770 | 771 | self.profileIndex = 0 |
|
|
771 | 772 | |
|
|
772 | 773 | # self.utctime = None |
|
|
773 | 774 | # self.timeZone = None |
|
|
774 | 775 | # self.ltctime = None |
|
|
775 | 776 | # self.timeInterval = None |
|
|
776 | 777 | # self.header = None |
|
|
777 | 778 | # self.data_header = None |
|
|
778 | 779 | # self.data = None |
|
|
779 | 780 | # self.datatime = None |
|
|
780 | 781 | # self.flagNoData = False |
|
|
781 | 782 | # self.expName = '' |
|
|
782 | 783 | # self.nChannels = None |
|
|
783 | 784 | # self.nSamples = None |
|
|
784 | 785 | # self.dataBlocksPerFile = None |
|
|
785 | 786 | # self.comments = '' |
|
|
786 | 787 | # |
|
|
787 | 788 | |
|
|
788 | 789 | def getltctime(self): |
|
|
789 | 790 | |
|
|
790 | 791 | if self.useLocalTime: |
|
|
791 | 792 | return self.utctime - self.timeZone * 60 |
|
|
792 | 793 | |
|
|
793 | 794 | return self.utctime |
|
|
794 | 795 | |
|
|
795 | 796 | def getDatatime(self): |
|
|
796 | 797 | |
|
|
797 | 798 | datatime = datetime.datetime.utcfromtimestamp(self.ltctime) |
|
|
798 | 799 | return datatime |
|
|
799 | 800 | |
|
|
800 | 801 | def getTimeRange(self): |
|
|
801 | 802 | |
|
|
802 | 803 | datatime = [] |
|
|
803 | 804 | |
|
|
804 | 805 | datatime.append(self.ltctime) |
|
|
805 | 806 | datatime.append(self.ltctime + self.timeInterval) |
|
|
806 | 807 | |
|
|
807 | 808 | datatime = numpy.array(datatime) |
|
|
808 | 809 | |
|
|
809 | 810 | return datatime |
|
|
810 | 811 | |
|
|
811 | 812 | def getHeiRange(self): |
|
|
812 | 813 | |
|
|
813 | 814 | heis = self.heightList |
|
|
814 | 815 | |
|
|
815 | 816 | return heis |
|
|
816 | 817 | |
|
|
817 | 818 | def getNHeights(self): |
|
|
818 | 819 | |
|
|
819 | 820 | return len(self.heightList) |
|
|
820 | 821 | |
|
|
821 | 822 | def getNChannels(self): |
|
|
822 | 823 | |
|
|
823 | 824 | return len(self.channelList) |
|
|
824 | 825 | |
|
|
825 | 826 | def getChannelIndexList(self): |
|
|
826 | 827 | |
|
|
827 | 828 | return list(range(self.nChannels)) |
|
|
828 | 829 | |
|
|
829 | 830 | def getNoise(self, type=1): |
|
|
830 | 831 | |
|
|
831 | 832 | #noise = numpy.zeros(self.nChannels) |
|
|
832 | 833 | |
|
|
833 | 834 | if type == 1: |
|
|
834 | 835 | noise = self.getNoisebyHildebrand() |
|
|
835 | 836 | |
|
|
836 | 837 | if type == 2: |
|
|
837 | 838 | noise = self.getNoisebySort() |
|
|
838 | 839 | |
|
|
839 | 840 | if type == 3: |
|
|
840 | 841 | noise = self.getNoisebyWindow() |
|
|
841 | 842 | |
|
|
842 | 843 | return noise |
|
|
843 | 844 | |
|
|
844 | 845 | def getTimeInterval(self): |
|
|
845 | 846 | |
|
|
846 | 847 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt |
|
|
847 | 848 | |
|
|
848 | 849 | return timeInterval |
|
|
849 | 850 | |
|
|
850 | 851 | def get_ippSeconds(self): |
|
|
851 | 852 | ''' |
|
|
852 | 853 | ''' |
|
|
853 | 854 | return self.ipp_sec |
|
|
854 | 855 | |
|
|
855 | 856 | |
|
|
856 | 857 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
|
857 | 858 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
|
|
858 | 859 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
|
|
859 | 860 | channelIndexList = property( |
|
|
860 | 861 | getChannelIndexList, "I'm the 'channelIndexList' property.") |
|
|
861 | 862 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
862 | 863 | |
|
|
863 | 864 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
|
864 | 865 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
865 | 866 | ippSeconds = property(get_ippSeconds, '') |
|
|
866 | 867 | |
|
|
867 | 868 | class Correlation(JROData): |
|
|
868 | 869 | |
|
|
869 | 870 | noise = None |
|
|
870 | 871 | SNR = None |
|
|
871 | 872 | #-------------------------------------------------- |
|
|
872 | 873 | mode = None |
|
|
873 | 874 | split = False |
|
|
874 | 875 | data_cf = None |
|
|
875 | 876 | lags = None |
|
|
876 | 877 | lagRange = None |
|
|
877 | 878 | pairsList = None |
|
|
878 | 879 | normFactor = None |
|
|
879 | 880 | #-------------------------------------------------- |
|
|
880 | 881 | # calculateVelocity = None |
|
|
881 | 882 | nLags = None |
|
|
882 | 883 | nPairs = None |
|
|
883 | 884 | nAvg = None |
|
|
884 | 885 | |
|
|
885 | 886 | def __init__(self): |
|
|
886 | 887 | ''' |
|
|
887 | 888 | Constructor |
|
|
888 | 889 | ''' |
|
|
889 | 890 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
890 | 891 | |
|
|
891 | 892 | self.systemHeaderObj = SystemHeader() |
|
|
892 | 893 | |
|
|
893 | 894 | self.type = "Correlation" |
|
|
894 | 895 | |
|
|
895 | 896 | self.data = None |
|
|
896 | 897 | |
|
|
897 | 898 | self.dtype = None |
|
|
898 | 899 | |
|
|
899 | 900 | self.nProfiles = None |
|
|
900 | 901 | |
|
|
901 | 902 | self.heightList = None |
|
|
902 | 903 | |
|
|
903 | 904 | self.channelList = None |
|
|
904 | 905 | |
|
|
905 | 906 | self.flagNoData = True |
|
|
906 | 907 | |
|
|
907 | 908 | self.flagDiscontinuousBlock = False |
|
|
908 | 909 | |
|
|
909 | 910 | self.utctime = None |
|
|
910 | 911 | |
|
|
911 | 912 | self.timeZone = None |
|
|
912 | 913 | |
|
|
913 | 914 | self.dstFlag = None |
|
|
914 | 915 | |
|
|
915 | 916 | self.errorCount = None |
|
|
916 | 917 | |
|
|
917 | 918 | self.blocksize = None |
|
|
918 | 919 | |
|
|
919 | 920 | self.flagDecodeData = False # asumo q la data no esta decodificada |
|
|
920 | 921 | |
|
|
921 | 922 | self.flagDeflipData = False # asumo q la data no esta sin flip |
|
|
922 | 923 | |
|
|
923 | 924 | self.pairsList = None |
|
|
924 | 925 | |
|
|
925 | 926 | self.nPoints = None |
|
|
926 | 927 | |
|
|
927 | 928 | def getPairsList(self): |
|
|
928 | 929 | |
|
|
929 | 930 | return self.pairsList |
|
|
930 | 931 | |
|
|
931 | 932 | def getNoise(self, mode=2): |
|
|
932 | 933 | |
|
|
933 | 934 | indR = numpy.where(self.lagR == 0)[0][0] |
|
|
934 | 935 | indT = numpy.where(self.lagT == 0)[0][0] |
|
|
935 | 936 | |
|
|
936 | 937 | jspectra0 = self.data_corr[:, :, indR, :] |
|
|
937 | 938 | jspectra = copy.copy(jspectra0) |
|
|
938 | 939 | |
|
|
939 | 940 | num_chan = jspectra.shape[0] |
|
|
940 | 941 | num_hei = jspectra.shape[2] |
|
|
941 | 942 | |
|
|
942 | 943 | freq_dc = jspectra.shape[1] / 2 |
|
|
943 | 944 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc |
|
|
944 | 945 | |
|
|
945 | 946 | if ind_vel[0] < 0: |
|
|
946 | 947 | ind_vel[list(range(0, 1))] = ind_vel[list( |
|
|
947 | 948 | range(0, 1))] + self.num_prof |
|
|
948 | 949 | |
|
|
949 | 950 | if mode == 1: |
|
|
950 | 951 | jspectra[:, freq_dc, :] = ( |
|
|
951 | 952 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION |
|
|
952 | 953 | |
|
|
953 | 954 | if mode == 2: |
|
|
954 | 955 | |
|
|
955 | 956 | vel = numpy.array([-2, -1, 1, 2]) |
|
|
956 | 957 | xx = numpy.zeros([4, 4]) |
|
|
957 | 958 | |
|
|
958 | 959 | for fil in range(4): |
|
|
959 | 960 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) |
|
|
960 | 961 | |
|
|
961 | 962 | xx_inv = numpy.linalg.inv(xx) |
|
|
962 | 963 | xx_aux = xx_inv[0, :] |
|
|
963 | 964 | |
|
|
964 | 965 | for ich in range(num_chan): |
|
|
965 | 966 | yy = jspectra[ich, ind_vel, :] |
|
|
966 | 967 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
|
967 | 968 | |
|
|
968 | 969 | junkid = jspectra[ich, freq_dc, :] <= 0 |
|
|
969 | 970 | cjunkid = sum(junkid) |
|
|
970 | 971 | |
|
|
971 | 972 | if cjunkid.any(): |
|
|
972 | 973 | jspectra[ich, freq_dc, junkid.nonzero()] = ( |
|
|
973 | 974 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 |
|
|
974 | 975 | |
|
|
975 | 976 | noise = jspectra0[:, freq_dc, :] - jspectra[:, freq_dc, :] |
|
|
976 | 977 | |
|
|
977 | 978 | return noise |
|
|
978 | 979 | |
|
|
979 | 980 | def getTimeInterval(self): |
|
|
980 | 981 | |
|
|
981 | 982 | timeInterval = self.ippSeconds * self.nCohInt * self.nProfiles |
|
|
982 | 983 | |
|
|
983 | 984 | return timeInterval |
|
|
984 | 985 | |
|
|
985 | 986 | def splitFunctions(self): |
|
|
986 | 987 | |
|
|
987 | 988 | pairsList = self.pairsList |
|
|
988 | 989 | ccf_pairs = [] |
|
|
989 | 990 | acf_pairs = [] |
|
|
990 | 991 | ccf_ind = [] |
|
|
991 | 992 | acf_ind = [] |
|
|
992 | 993 | for l in range(len(pairsList)): |
|
|
993 | 994 | chan0 = pairsList[l][0] |
|
|
994 | 995 | chan1 = pairsList[l][1] |
|
|
995 | 996 | |
|
|
996 | 997 | # Obteniendo pares de Autocorrelacion |
|
|
997 | 998 | if chan0 == chan1: |
|
|
998 | 999 | acf_pairs.append(chan0) |
|
|
999 | 1000 | acf_ind.append(l) |
|
|
1000 | 1001 | else: |
|
|
1001 | 1002 | ccf_pairs.append(pairsList[l]) |
|
|
1002 | 1003 | ccf_ind.append(l) |
|
|
1003 | 1004 | |
|
|
1004 | 1005 | data_acf = self.data_cf[acf_ind] |
|
|
1005 | 1006 | data_ccf = self.data_cf[ccf_ind] |
|
|
1006 | 1007 | |
|
|
1007 | 1008 | return acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf |
|
|
1008 | 1009 | |
|
|
1009 | 1010 | def getNormFactor(self): |
|
|
1010 | 1011 | acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.splitFunctions() |
|
|
1011 | 1012 | acf_pairs = numpy.array(acf_pairs) |
|
|
1012 | 1013 | normFactor = numpy.zeros((self.nPairs, self.nHeights)) |
|
|
1013 | 1014 | |
|
|
1014 | 1015 | for p in range(self.nPairs): |
|
|
1015 | 1016 | pair = self.pairsList[p] |
|
|
1016 | 1017 | |
|
|
1017 | 1018 | ch0 = pair[0] |
|
|
1018 | 1019 | ch1 = pair[1] |
|
|
1019 | 1020 | |
|
|
1020 | 1021 | ch0_max = numpy.max(data_acf[acf_pairs == ch0, :, :], axis=1) |
|
|
1021 | 1022 | ch1_max = numpy.max(data_acf[acf_pairs == ch1, :, :], axis=1) |
|
|
1022 | 1023 | normFactor[p, :] = numpy.sqrt(ch0_max * ch1_max) |
|
|
1023 | 1024 | |
|
|
1024 | 1025 | return normFactor |
|
|
1025 | 1026 | |
|
|
1026 | 1027 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
1027 | 1028 | normFactor = property(getNormFactor, "I'm the 'normFactor property'") |
|
|
1028 | 1029 | |
|
|
1029 | 1030 | |
|
|
1030 | 1031 | class Parameters(Spectra): |
|
|
1031 | 1032 | |
|
|
1032 | 1033 | experimentInfo = None # Information about the experiment |
|
|
1033 | 1034 | # Information from previous data |
|
|
1034 | 1035 | inputUnit = None # Type of data to be processed |
|
|
1035 | 1036 | operation = None # Type of operation to parametrize |
|
|
1036 | 1037 | # normFactor = None #Normalization Factor |
|
|
1037 | 1038 | groupList = None # List of Pairs, Groups, etc |
|
|
1038 | 1039 | # Parameters |
|
|
1039 | 1040 | data_param = None # Parameters obtained |
|
|
1040 | 1041 | data_pre = None # Data Pre Parametrization |
|
|
1041 | 1042 | data_SNR = None # Signal to Noise Ratio |
|
|
1042 | 1043 | # heightRange = None #Heights |
|
|
1043 | 1044 | abscissaList = None # Abscissa, can be velocities, lags or time |
|
|
1044 | 1045 | # noise = None #Noise Potency |
|
|
1045 | 1046 | utctimeInit = None # Initial UTC time |
|
|
1046 | 1047 | paramInterval = None # Time interval to calculate Parameters in seconds |
|
|
1047 | 1048 | useLocalTime = True |
|
|
1048 | 1049 | # Fitting |
|
|
1049 | 1050 | data_error = None # Error of the estimation |
|
|
1050 | 1051 | constants = None |
|
|
1051 | 1052 | library = None |
|
|
1052 | 1053 | # Output signal |
|
|
1053 | 1054 | outputInterval = None # Time interval to calculate output signal in seconds |
|
|
1054 | 1055 | data_output = None # Out signal |
|
|
1055 | 1056 | nAvg = None |
|
|
1056 | 1057 | noise_estimation = None |
|
|
1057 | 1058 | GauSPC = None # Fit gaussian SPC |
|
|
1058 | 1059 | |
|
|
1059 | 1060 | def __init__(self): |
|
|
1060 | 1061 | ''' |
|
|
1061 | 1062 | Constructor |
|
|
1062 | 1063 | ''' |
|
|
1063 | 1064 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
1064 | 1065 | |
|
|
1065 | 1066 | self.systemHeaderObj = SystemHeader() |
|
|
1066 | 1067 | |
|
|
1067 | 1068 | self.type = "Parameters" |
|
|
1068 | 1069 | |
|
|
1069 | 1070 | def getTimeRange1(self, interval): |
|
|
1070 | 1071 | |
|
|
1071 | 1072 | datatime = [] |
|
|
1072 | 1073 | |
|
|
1073 | 1074 | if self.useLocalTime: |
|
|
1074 | 1075 | time1 = self.utctimeInit - self.timeZone * 60 |
|
|
1075 | 1076 | else: |
|
|
1076 | 1077 | time1 = self.utctimeInit |
|
|
1077 | 1078 | |
|
|
1078 | 1079 | datatime.append(time1) |
|
|
1079 | 1080 | datatime.append(time1 + interval) |
|
|
1080 | 1081 | datatime = numpy.array(datatime) |
|
|
1081 | 1082 | |
|
|
1082 | 1083 | return datatime |
|
|
1083 | 1084 | |
|
|
1084 | 1085 | def getTimeInterval(self): |
|
|
1085 | 1086 | |
|
|
1086 | 1087 | if hasattr(self, 'timeInterval1'): |
|
|
1087 | 1088 | return self.timeInterval1 |
|
|
1088 | 1089 | else: |
|
|
1089 | 1090 | return self.paramInterval |
|
|
1090 | 1091 | |
|
|
1091 | 1092 | def setValue(self, value): |
|
|
1092 | 1093 | |
|
|
1093 | 1094 | print("This property should not be initialized") |
|
|
1094 | 1095 | |
|
|
1095 | 1096 | return |
|
|
1096 | 1097 | |
|
|
1097 | 1098 | def getNoise(self): |
|
|
1098 | 1099 | |
|
|
1099 | 1100 | return self.spc_noise |
|
|
1100 | 1101 | |
|
|
1101 | 1102 | timeInterval = property(getTimeInterval) |
|
|
1102 | 1103 | noise = property(getNoise, setValue, "I'm the 'Noise' property.") |
|
|
1103 | 1104 | |
|
|
1104 | 1105 | |
|
|
1105 | 1106 | class PlotterData(object): |
|
|
1106 | 1107 | ''' |
|
|
1107 | 1108 | Object to hold data to be plotted |
|
|
1108 | 1109 | ''' |
|
|
1109 | 1110 | |
|
|
1110 | 1111 | MAXNUMX = 100 |
|
|
1111 | 1112 | MAXNUMY = 100 |
|
|
1112 | 1113 | |
|
|
1113 | 1114 | def __init__(self, code, throttle_value, exp_code, buffering=True, snr=False): |
|
|
1114 | ||
|
|
1115 | ||
|
|
1115 | 1116 | self.key = code |
|
|
1116 | 1117 | self.throttle = throttle_value |
|
|
1117 | 1118 | self.exp_code = exp_code |
|
|
1118 | 1119 | self.buffering = buffering |
|
|
1119 | 1120 | self.ready = False |
|
|
1120 | 1121 | self.flagNoData = False |
|
|
1121 | 1122 | self.localtime = False |
|
|
1122 | 1123 | self.data = {} |
|
|
1123 | 1124 | self.meta = {} |
|
|
1124 | 1125 | self.__times = [] |
|
|
1125 | 1126 | self.__heights = [] |
|
|
1126 | 1127 | |
|
|
1127 | 1128 | if 'snr' in code: |
|
|
1128 | 1129 | self.plottypes = ['snr'] |
|
|
1129 | 1130 | elif code == 'spc': |
|
|
1130 | 1131 | self.plottypes = ['spc', 'noise', 'rti'] |
|
|
1131 | 1132 | elif code == 'rti': |
|
|
1132 | 1133 | self.plottypes = ['noise', 'rti'] |
|
|
1133 | 1134 | else: |
|
|
1134 | 1135 | self.plottypes = [code] |
|
|
1135 | 1136 | |
|
|
1136 | 1137 | if 'snr' not in self.plottypes and snr: |
|
|
1137 | 1138 | self.plottypes.append('snr') |
|
|
1138 | 1139 | |
|
|
1139 | 1140 | for plot in self.plottypes: |
|
|
1140 | 1141 | self.data[plot] = {} |
|
|
1141 | 1142 | |
|
|
1143 | ||
|
|
1142 | 1144 | def __str__(self): |
|
|
1143 | 1145 | dum = ['{}{}'.format(key, self.shape(key)) for key in self.data] |
|
|
1144 | 1146 | return 'Data[{}][{}]'.format(';'.join(dum), len(self.__times)) |
|
|
1145 | 1147 | |
|
|
1146 | 1148 | def __len__(self): |
|
|
1147 | 1149 | return len(self.__times) |
|
|
1148 | 1150 | |
|
|
1149 | 1151 | def __getitem__(self, key): |
|
|
1150 | ||
|
|
1152 | ||
|
|
1151 | 1153 | if key not in self.data: |
|
|
1152 | 1154 | raise KeyError(log.error('Missing key: {}'.format(key))) |
|
|
1153 | 1155 | if 'spc' in key or not self.buffering: |
|
|
1154 | 1156 | ret = self.data[key] |
|
|
1155 | 1157 | elif 'scope' in key: |
|
|
1156 | 1158 | ret = numpy.array(self.data[key][float(self.tm)]) |
|
|
1157 | 1159 | else: |
|
|
1158 | 1160 | ret = numpy.array([self.data[key][x] for x in self.times]) |
|
|
1159 | 1161 | if ret.ndim > 1: |
|
|
1160 | 1162 | ret = numpy.swapaxes(ret, 0, 1) |
|
|
1161 | 1163 | return ret |
|
|
1162 | 1164 | |
|
|
1163 | 1165 | def __contains__(self, key): |
|
|
1164 | 1166 | return key in self.data |
|
|
1165 | 1167 | |
|
|
1166 | 1168 | def setup(self): |
|
|
1167 | 1169 | ''' |
|
|
1168 | 1170 | Configure object |
|
|
1169 | 1171 | ''' |
|
|
1170 | ||
|
|
1171 | 1172 | self.type = '' |
|
|
1172 | 1173 | self.ready = False |
|
|
1173 | 1174 | self.data = {} |
|
|
1174 | 1175 | self.__times = [] |
|
|
1175 | 1176 | self.__heights = [] |
|
|
1176 | 1177 | self.__all_heights = set() |
|
|
1177 | 1178 | for plot in self.plottypes: |
|
|
1178 | 1179 | if 'snr' in plot: |
|
|
1179 | 1180 | plot = 'snr' |
|
|
1180 | 1181 | elif 'spc_moments' == plot: |
|
|
1181 | 1182 | plot = 'moments' |
|
|
1182 | 1183 | self.data[plot] = {} |
|
|
1183 | ||
|
|
1184 | ||
|
|
1184 | 1185 | if 'spc' in self.data or 'rti' in self.data or 'cspc' in self.data or 'moments' in self.data: |
|
|
1185 | 1186 | self.data['noise'] = {} |
|
|
1186 | 1187 | self.data['rti'] = {} |
|
|
1187 | 1188 | if 'noise' not in self.plottypes: |
|
|
1188 | 1189 | self.plottypes.append('noise') |
|
|
1189 | 1190 | if 'rti' not in self.plottypes: |
|
|
1190 | 1191 | self.plottypes.append('rti') |
|
|
1191 | ||
|
|
1192 | ||
|
|
1192 | 1193 | def shape(self, key): |
|
|
1193 | 1194 | ''' |
|
|
1194 | 1195 | Get the shape of the one-element data for the given key |
|
|
1195 | 1196 | ''' |
|
|
1196 | 1197 | |
|
|
1197 | 1198 | if len(self.data[key]): |
|
|
1198 | 1199 | if 'spc' in key or not self.buffering: |
|
|
1199 | 1200 | return self.data[key].shape |
|
|
1200 | 1201 | return self.data[key][self.__times[0]].shape |
|
|
1201 | 1202 | return (0,) |
|
|
1202 | 1203 | |
|
|
1203 | 1204 | def update(self, dataOut, tm): |
|
|
1204 | 1205 | ''' |
|
|
1205 | 1206 | Update data object with new dataOut |
|
|
1206 | 1207 | ''' |
|
|
1207 | ||
|
|
1208 | 1208 | if tm in self.__times: |
|
|
1209 | 1209 | return |
|
|
1210 | 1210 | self.profileIndex = dataOut.profileIndex |
|
|
1211 | 1211 | self.tm = tm |
|
|
1212 | 1212 | self.type = dataOut.type |
|
|
1213 | 1213 | self.parameters = getattr(dataOut, 'parameters', []) |
|
|
1214 | ||
|
|
1214 | ||
|
|
1215 | 1215 | if hasattr(dataOut, 'meta'): |
|
|
1216 | 1216 | self.meta.update(dataOut.meta) |
|
|
1217 | ||
|
|
1217 | ||
|
|
1218 | 1218 | if hasattr(dataOut, 'pairsList'): |
|
|
1219 | 1219 | self.pairs = dataOut.pairsList |
|
|
1220 | ||
|
|
1220 | ||
|
|
1221 | 1221 | self.interval = dataOut.getTimeInterval() |
|
|
1222 | 1222 | self.localtime = dataOut.useLocalTime |
|
|
1223 | 1223 | if True in ['spc' in ptype for ptype in self.plottypes]: |
|
|
1224 | 1224 | self.xrange = (dataOut.getFreqRange(1)/1000., |
|
|
1225 | 1225 | dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
|
|
1226 | 1226 | self.factor = dataOut.normFactor |
|
|
1227 | 1227 | self.__heights.append(dataOut.heightList) |
|
|
1228 | 1228 | self.__all_heights.update(dataOut.heightList) |
|
|
1229 | 1229 | self.__times.append(tm) |
|
|
1230 | ||
|
|
1231 | 1230 | for plot in self.plottypes: |
|
|
1232 | 1231 | if plot in ('spc', 'spc_moments', 'spc_cut'): |
|
|
1233 | 1232 | z = dataOut.data_spc/dataOut.normFactor |
|
|
1234 | 1233 | buffer = 10*numpy.log10(z) |
|
|
1235 | 1234 | if plot == 'cspc': |
|
|
1236 | 1235 | z = dataOut.data_spc/dataOut.normFactor |
|
|
1237 | 1236 | buffer = (dataOut.data_spc, dataOut.data_cspc) |
|
|
1238 | 1237 | if plot == 'noise': |
|
|
1239 | 1238 | buffer = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) |
|
|
1240 | 1239 | if plot in ('rti', 'spcprofile'): |
|
|
1241 | 1240 | buffer = dataOut.getPower() |
|
|
1242 | 1241 | if plot == 'snr_db': |
|
|
1243 | 1242 | buffer = dataOut.data_SNR |
|
|
1244 | 1243 | if plot == 'snr': |
|
|
1245 | 1244 | buffer = 10*numpy.log10(dataOut.data_SNR) |
|
|
1246 | 1245 | if plot == 'dop': |
|
|
1247 | 1246 | buffer = dataOut.data_DOP |
|
|
1248 | 1247 | if plot == 'pow': |
|
|
1249 | 1248 | buffer = 10*numpy.log10(dataOut.data_POW) |
|
|
1250 | 1249 | if plot == 'width': |
|
|
1251 | 1250 | buffer = dataOut.data_WIDTH |
|
|
1252 | 1251 | if plot == 'coh': |
|
|
1253 | 1252 | buffer = dataOut.getCoherence() |
|
|
1254 | 1253 | if plot == 'phase': |
|
|
1255 | 1254 | buffer = dataOut.getCoherence(phase=True) |
|
|
1256 | 1255 | if plot == 'output': |
|
|
1257 | 1256 | buffer = dataOut.data_output |
|
|
1258 | 1257 | if plot == 'param': |
|
|
1259 | 1258 | buffer = dataOut.data_param |
|
|
1260 | 1259 | if plot == 'scope': |
|
|
1261 | 1260 | buffer = dataOut.data |
|
|
1262 | 1261 | self.flagDataAsBlock = dataOut.flagDataAsBlock |
|
|
1263 |
self.nProfiles = dataOut.nProfiles |
|
|
|
1264 | ||
|
|
1262 | self.nProfiles = dataOut.nProfiles | |
|
|
1263 | if plot == 'pp_power': | |
|
|
1264 | buffer = dataOut.data_intensity | |
|
|
1265 | self.flagDataAsBlock = dataOut.flagDataAsBlock | |
|
|
1266 | self.nProfiles = dataOut.nProfiles | |
|
|
1267 | if plot == 'pp_velocity': | |
|
|
1268 | buffer = dataOut.data_velocity | |
|
|
1269 | self.flagDataAsBlock = dataOut.flagDataAsBlock | |
|
|
1270 | self.nProfiles = dataOut.nProfiles | |
|
|
1271 | ||
|
|
1265 | 1272 | if plot == 'spc': |
|
|
1266 | 1273 | self.data['spc'] = buffer |
|
|
1267 | 1274 | elif plot == 'cspc': |
|
|
1268 | 1275 | self.data['spc'] = buffer[0] |
|
|
1269 | 1276 | self.data['cspc'] = buffer[1] |
|
|
1270 | 1277 | elif plot == 'spc_moments': |
|
|
1271 | 1278 | self.data['spc'] = buffer |
|
|
1272 | 1279 | self.data['moments'][tm] = dataOut.moments |
|
|
1273 | 1280 | else: |
|
|
1274 | 1281 | if self.buffering: |
|
|
1275 | 1282 | self.data[plot][tm] = buffer |
|
|
1276 | 1283 | else: |
|
|
1277 | 1284 | self.data[plot] = buffer |
|
|
1278 | 1285 | |
|
|
1279 | 1286 | if dataOut.channelList is None: |
|
|
1280 | 1287 | self.channels = range(buffer.shape[0]) |
|
|
1281 | 1288 | else: |
|
|
1282 | 1289 | self.channels = dataOut.channelList |
|
|
1283 | 1290 | |
|
|
1284 | 1291 | if buffer is None: |
|
|
1285 | 1292 | self.flagNoData = True |
|
|
1286 |
raise schainpy.admin.SchainWarning('Attribute data_{} is empty'.format(self.key)) |
|
|
|
1293 | raise schainpy.admin.SchainWarning('Attribute data_{} is empty'.format(self.key)) | |
|
|
1287 | 1294 | |
|
|
1288 | 1295 | def normalize_heights(self): |
|
|
1289 | 1296 | ''' |
|
|
1290 | 1297 | Ensure same-dimension of the data for different heighList |
|
|
1291 | 1298 | ''' |
|
|
1292 | 1299 | |
|
|
1293 | 1300 | H = numpy.array(list(self.__all_heights)) |
|
|
1294 | 1301 | H.sort() |
|
|
1295 | 1302 | for key in self.data: |
|
|
1296 | 1303 | shape = self.shape(key)[:-1] + H.shape |
|
|
1297 | 1304 | for tm, obj in list(self.data[key].items()): |
|
|
1298 | 1305 | h = self.__heights[self.__times.index(tm)] |
|
|
1299 | 1306 | if H.size == h.size: |
|
|
1300 | 1307 | continue |
|
|
1301 | 1308 | index = numpy.where(numpy.in1d(H, h))[0] |
|
|
1302 | 1309 | dummy = numpy.zeros(shape) + numpy.nan |
|
|
1303 | 1310 | if len(shape) == 2: |
|
|
1304 | 1311 | dummy[:, index] = obj |
|
|
1305 | 1312 | else: |
|
|
1306 | 1313 | dummy[index] = obj |
|
|
1307 | 1314 | self.data[key][tm] = dummy |
|
|
1308 | 1315 | |
|
|
1309 | 1316 | self.__heights = [H for tm in self.__times] |
|
|
1310 | 1317 | |
|
|
1311 | 1318 | def jsonify(self, plot_name, plot_type, decimate=False): |
|
|
1312 | 1319 | ''' |
|
|
1313 | 1320 | Convert data to json |
|
|
1314 | 1321 | ''' |
|
|
1315 | 1322 | |
|
|
1316 | 1323 | tm = self.times[-1] |
|
|
1317 | 1324 | dy = int(self.heights.size/self.MAXNUMY) + 1 |
|
|
1318 | 1325 | if self.key in ('spc', 'cspc') or not self.buffering: |
|
|
1319 | 1326 | dx = int(self.data[self.key].shape[1]/self.MAXNUMX) + 1 |
|
|
1320 | 1327 | data = self.roundFloats( |
|
|
1321 | 1328 | self.data[self.key][::, ::dx, ::dy].tolist()) |
|
|
1322 | 1329 | else: |
|
|
1323 | 1330 | data = self.roundFloats(self.data[self.key][tm].tolist()) |
|
|
1324 | 1331 | if self.key is 'noise': |
|
|
1325 | 1332 | data = [[x] for x in data] |
|
|
1326 | 1333 | |
|
|
1327 | 1334 | meta = {} |
|
|
1328 | 1335 | ret = { |
|
|
1329 | 1336 | 'plot': plot_name, |
|
|
1330 | 1337 | 'code': self.exp_code, |
|
|
1331 | 1338 | 'time': float(tm), |
|
|
1332 | 1339 | 'data': data, |
|
|
1333 | 1340 | } |
|
|
1334 | 1341 | meta['type'] = plot_type |
|
|
1335 | 1342 | meta['interval'] = float(self.interval) |
|
|
1336 | 1343 | meta['localtime'] = self.localtime |
|
|
1337 | 1344 | meta['yrange'] = self.roundFloats(self.heights[::dy].tolist()) |
|
|
1338 | 1345 | if 'spc' in self.data or 'cspc' in self.data: |
|
|
1339 | 1346 | meta['xrange'] = self.roundFloats(self.xrange[2][::dx].tolist()) |
|
|
1340 | 1347 | else: |
|
|
1341 | 1348 | meta['xrange'] = [] |
|
|
1342 | 1349 | |
|
|
1343 |
meta.update(self.meta) |
|
|
|
1350 | meta.update(self.meta) | |
|
|
1344 | 1351 | ret['metadata'] = meta |
|
|
1345 | 1352 | return json.dumps(ret) |
|
|
1346 | 1353 | |
|
|
1347 | 1354 | @property |
|
|
1348 | 1355 | def times(self): |
|
|
1349 | 1356 | ''' |
|
|
1350 | 1357 | Return the list of times of the current data |
|
|
1351 | 1358 | ''' |
|
|
1352 | 1359 | |
|
|
1353 | 1360 | ret = numpy.array(self.__times) |
|
|
1354 | 1361 | ret.sort() |
|
|
1355 | 1362 | return ret |
|
|
1356 | 1363 | |
|
|
1357 | 1364 | @property |
|
|
1358 | 1365 | def min_time(self): |
|
|
1359 | 1366 | ''' |
|
|
1360 | 1367 | Return the minimun time value |
|
|
1361 | 1368 | ''' |
|
|
1362 | 1369 | |
|
|
1363 | 1370 | return self.times[0] |
|
|
1364 | 1371 | |
|
|
1365 | 1372 | @property |
|
|
1366 | 1373 | def max_time(self): |
|
|
1367 | 1374 | ''' |
|
|
1368 | 1375 | Return the maximun time value |
|
|
1369 | 1376 | ''' |
|
|
1370 | 1377 | |
|
|
1371 | 1378 | return self.times[-1] |
|
|
1372 | 1379 | |
|
|
1373 | 1380 | @property |
|
|
1374 | 1381 | def heights(self): |
|
|
1375 | 1382 | ''' |
|
|
1376 | 1383 | Return the list of heights of the current data |
|
|
1377 | 1384 | ''' |
|
|
1378 | 1385 | |
|
|
1379 | 1386 | return numpy.array(self.__heights[-1]) |
|
|
1380 | 1387 | |
|
|
1381 | 1388 | @staticmethod |
|
|
1382 | 1389 | def roundFloats(obj): |
|
|
1383 | 1390 | if isinstance(obj, list): |
|
|
1384 | 1391 | return list(map(PlotterData.roundFloats, obj)) |
|
|
1385 | 1392 | elif isinstance(obj, float): |
|
|
1386 | 1393 | return round(obj, 2) |
| @@ -1,134 +1,233 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | Created on Jul 9, 2014 |
|
|
3 | 3 | |
|
|
4 | 4 | @author: roj-idl71 |
|
|
5 | 5 | ''' |
|
|
6 | 6 | import os |
|
|
7 | 7 | import datetime |
|
|
8 | 8 | import numpy |
|
|
9 | 9 | |
|
|
10 | 10 | from schainpy.model.graphics.jroplot_base import Plot, plt |
|
|
11 | 11 | |
|
|
12 | 12 | |
|
|
13 | 13 | class ScopePlot(Plot): |
|
|
14 | 14 | |
|
|
15 | 15 | ''' |
|
|
16 | 16 | Plot for Scope |
|
|
17 |
''' |
|
|
|
17 | ''' | |
|
|
18 | 18 | |
|
|
19 | 19 | CODE = 'scope' |
|
|
20 | 20 | plot_name = 'Scope' |
|
|
21 | 21 | plot_type = 'scatter' |
|
|
22 | ||
|
|
22 | ||
|
|
23 | 23 | def setup(self): |
|
|
24 | 24 | |
|
|
25 | 25 | self.xaxis = 'Range (Km)' |
|
|
26 | 26 | self.ncols = 1 |
|
|
27 | 27 | self.nrows = 1 |
|
|
28 | 28 | self.nplots = 1 |
|
|
29 | 29 | self.ylabel = 'Intensity [dB]' |
|
|
30 | 30 | self.titles = ['Scope'] |
|
|
31 | 31 | self.colorbar = False |
|
|
32 | 32 | self.width = 6 |
|
|
33 | 33 | self.height = 4 |
|
|
34 | 34 | |
|
|
35 | 35 | def plot_iq(self, x, y, channelIndexList, thisDatetime, wintitle): |
|
|
36 | ||
|
|
36 | ||
|
|
37 | 37 | yreal = y[channelIndexList,:].real |
|
|
38 | 38 | yimag = y[channelIndexList,:].imag |
|
|
39 | 39 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
40 | 40 | self.xlabel = "Range (Km)" |
|
|
41 | 41 | self.ylabel = "Intensity - IQ" |
|
|
42 | ||
|
|
42 | ||
|
|
43 | 43 | self.y = yreal |
|
|
44 | 44 | self.x = x |
|
|
45 | 45 | self.xmin = min(x) |
|
|
46 | 46 | self.xmax = max(x) |
|
|
47 | ||
|
|
48 | 47 | |
|
|
49 | self.titles[0] = title | |
|
|
48 | ||
|
|
49 | self.titles[0] = title | |
|
|
50 | 50 | |
|
|
51 | 51 | for i,ax in enumerate(self.axes): |
|
|
52 | 52 | title = "Channel %d" %(i) |
|
|
53 | 53 | if ax.firsttime: |
|
|
54 | 54 | ax.plt_r = ax.plot(x, yreal[i,:], color='b')[0] |
|
|
55 | 55 | ax.plt_i = ax.plot(x, yimag[i,:], color='r')[0] |
|
|
56 | 56 | else: |
|
|
57 | 57 | ax.plt_r.set_data(x, yreal[i,:]) |
|
|
58 | 58 | ax.plt_i.set_data(x, yimag[i,:]) |
|
|
59 | ||
|
|
59 | ||
|
|
60 | 60 | def plot_power(self, x, y, channelIndexList, thisDatetime, wintitle): |
|
|
61 | 61 | y = y[channelIndexList,:] * numpy.conjugate(y[channelIndexList,:]) |
|
|
62 | 62 | yreal = y.real |
|
|
63 | yreal = 10*numpy.log10(yreal) | |
|
|
63 | 64 | self.y = yreal |
|
|
64 | 65 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
65 | 66 | self.xlabel = "Range (Km)" |
|
|
66 | 67 | self.ylabel = "Intensity" |
|
|
67 | 68 | self.xmin = min(x) |
|
|
68 | 69 | self.xmax = max(x) |
|
|
69 | ||
|
|
70 | ||
|
|
70 | ||
|
|
71 | ||
|
|
71 | 72 | self.titles[0] = title |
|
|
72 | 73 | |
|
|
73 | 74 | for i,ax in enumerate(self.axes): |
|
|
74 | 75 | title = "Channel %d" %(i) |
|
|
75 | ||
|
|
76 | ||
|
|
76 | 77 | ychannel = yreal[i,:] |
|
|
77 | ||
|
|
78 |
if ax.firsttime: |
|
|
|
78 | ||
|
|
79 | if ax.firsttime: | |
|
|
79 | 80 | ax.plt_r = ax.plot(x, ychannel)[0] |
|
|
80 | 81 | else: |
|
|
81 | 82 | #pass |
|
|
82 | 83 | ax.plt_r.set_data(x, ychannel) |
|
|
83 | ||
|
|
84 | ||
|
|
85 | def plot_weatherpower(self, x, y, channelIndexList, thisDatetime, wintitle): | |
|
|
86 | ||
|
|
87 | ||
|
|
88 | y = y[channelIndexList,:] | |
|
|
89 | yreal = y.real | |
|
|
90 | yreal = 10*numpy.log10(yreal) | |
|
|
91 | self.y = yreal | |
|
|
92 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
|
|
93 | self.xlabel = "Range (Km)" | |
|
|
94 | self.ylabel = "Intensity" | |
|
|
95 | self.xmin = min(x) | |
|
|
96 | self.xmax = max(x) | |
|
|
97 | ||
|
|
98 | self.titles[0] =title | |
|
|
99 | for i,ax in enumerate(self.axes): | |
|
|
100 | title = "Channel %d" %(i) | |
|
|
101 | ||
|
|
102 | ychannel = yreal[i,:] | |
|
|
103 | ||
|
|
104 | if ax.firsttime: | |
|
|
105 | ax.plt_r = ax.plot(x, ychannel)[0] | |
|
|
106 | else: | |
|
|
107 | #pass | |
|
|
108 | ax.plt_r.set_data(x, ychannel) | |
|
|
109 | ||
|
|
110 | def plot_weathervelocity(self, x, y, channelIndexList, thisDatetime, wintitle): | |
|
|
111 | ||
|
|
112 | x = x[channelIndexList,:] | |
|
|
113 | yreal = y | |
|
|
114 | self.y = yreal | |
|
|
115 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
|
|
116 | self.xlabel = "Velocity (m/s)" | |
|
|
117 | self.ylabel = "Range (Km)" | |
|
|
118 | self.xmin = numpy.min(x) | |
|
|
119 | self.xmax = numpy.max(x) | |
|
|
120 | self.titles[0] =title | |
|
|
121 | for i,ax in enumerate(self.axes): | |
|
|
122 | title = "Channel %d" %(i) | |
|
|
123 | xchannel = x[i,:] | |
|
|
124 | if ax.firsttime: | |
|
|
125 | ax.plt_r = ax.plot(xchannel, yreal)[0] | |
|
|
126 | else: | |
|
|
127 | #pass | |
|
|
128 | ax.plt_r.set_data(xchannel, yreal) | |
|
|
84 | 129 | |
|
|
85 | 130 | def plot(self): |
|
|
86 | ||
|
|
87 | 131 | if self.channels: |
|
|
88 | 132 | channels = self.channels |
|
|
89 | 133 | else: |
|
|
90 | 134 | channels = self.data.channels |
|
|
91 | 135 | |
|
|
92 | 136 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]) |
|
|
93 | ||
|
|
94 |
scope = self.data[' |
|
|
|
95 | ||
|
|
137 | if self.CODE == "pp_power": | |
|
|
138 | scope = self.data['pp_power'] | |
|
|
139 | elif self.CODE == "pp_velocity": | |
|
|
140 | scope = self.data["pp_velocity"] | |
|
|
141 | else: | |
|
|
142 | scope =self.data["scope"] | |
|
|
143 | ||
|
|
96 | 144 | if self.data.flagDataAsBlock: |
|
|
97 | ||
|
|
145 | ||
|
|
98 | 146 | for i in range(self.data.nProfiles): |
|
|
99 | 147 | |
|
|
100 | 148 | wintitle1 = " [Profile = %d] " %i |
|
|
101 | ||
|
|
102 | if self.type == "power": | |
|
|
103 |
self.plot_power(self.data.heights, |
|
|
|
104 |
scope[:,i,:], |
|
|
|
105 | channels, | |
|
|
106 |
thisDatetime, |
|
|
|
107 | wintitle1 | |
|
|
149 | if self.CODE =="scope": | |
|
|
150 | if self.type == "power": | |
|
|
151 | self.plot_power(self.data.heights, | |
|
|
152 | scope[:,i,:], | |
|
|
153 | channels, | |
|
|
154 | thisDatetime, | |
|
|
155 | wintitle1 | |
|
|
156 | ) | |
|
|
157 | ||
|
|
158 | if self.type == "iq": | |
|
|
159 | self.plot_iq(self.data.heights, | |
|
|
160 | scope[:,i,:], | |
|
|
161 | channels, | |
|
|
162 | thisDatetime, | |
|
|
163 | wintitle1 | |
|
|
108 | 164 | ) |
|
|
165 | if self.CODE=="pp_power": | |
|
|
166 | self.plot_weatherpower(self.data.heights, | |
|
|
167 | scope[:,i,:], | |
|
|
168 | channels, | |
|
|
169 | thisDatetime, | |
|
|
170 | wintitle | |
|
|
171 | ) | |
|
|
172 | if self.CODE=="pp_velocity": | |
|
|
173 | self.plot_weathervelocity(scope[:,i,:], | |
|
|
174 | self.data.heights, | |
|
|
175 | channels, | |
|
|
176 | thisDatetime, | |
|
|
177 | wintitle | |
|
|
178 | ) | |
|
|
179 | else: | |
|
|
180 | wintitle = " [Profile = %d] " %self.data.profileIndex | |
|
|
181 | if self.CODE== "scope": | |
|
|
182 | if self.type == "power": | |
|
|
183 | self.plot_power(self.data.heights, | |
|
|
184 | scope, | |
|
|
185 | channels, | |
|
|
186 | thisDatetime, | |
|
|
187 | wintitle | |
|
|
188 | ) | |
|
|
109 | 189 | |
|
|
110 | 190 | if self.type == "iq": |
|
|
111 |
self.plot_iq(self.data.heights, |
|
|
|
112 |
|
|
|
|
113 |
|
|
|
|
114 |
|
|
|
|
115 |
|
|
|
|
191 | self.plot_iq(self.data.heights, | |
|
|
192 | scope, | |
|
|
193 | channels, | |
|
|
194 | thisDatetime, | |
|
|
195 | wintitle | |
|
|
116 | 196 | ) |
|
|
117 | else: | |
|
|
118 | wintitle = " [Profile = %d] " %self.data.profileIndex | |
|
|
119 | ||
|
|
120 | if self.type == "power": | |
|
|
121 | self.plot_power(self.data.heights, | |
|
|
122 |
|
|
|
|
123 |
|
|
|
|
124 | thisDatetime, | |
|
|
125 | wintitle | |
|
|
126 |
|
|
|
|
127 | ||
|
|
128 | if self.type == "iq": | |
|
|
129 | self.plot_iq(self.data.heights, | |
|
|
130 |
|
|
|
|
131 | channels, | |
|
|
132 | thisDatetime, | |
|
|
133 | wintitle | |
|
|
134 | ) | |
|
|
197 | if self.CODE=="pp_power": | |
|
|
198 | self.plot_weatherpower(self.data.heights, | |
|
|
199 | scope, | |
|
|
200 | channels, | |
|
|
201 | thisDatetime, | |
|
|
202 | wintitle | |
|
|
203 | ) | |
|
|
204 | if self.CODE=="pp_velocity": | |
|
|
205 | self.plot_weathervelocity(scope, | |
|
|
206 | self.data.heights, | |
|
|
207 | channels, | |
|
|
208 | thisDatetime, | |
|
|
209 | wintitle | |
|
|
210 | ) | |
|
|
211 | ||
|
|
212 | ||
|
|
213 | ||
|
|
214 | class PulsepairPowerPlot(ScopePlot): | |
|
|
215 | ''' | |
|
|
216 | Plot for | |
|
|
217 | ''' | |
|
|
218 | ||
|
|
219 | CODE = 'pp_power' | |
|
|
220 | plot_name = 'PulsepairPower' | |
|
|
221 | plot_type = 'scatter' | |
|
|
222 | buffering = False | |
|
|
223 | ||
|
|
224 | ||
|
|
225 | ||
|
|
226 | class PulsepairVelocityPlot(ScopePlot): | |
|
|
227 | ''' | |
|
|
228 | Plot for | |
|
|
229 | ''' | |
|
|
230 | CODE = 'pp_velocity' | |
|
|
231 | plot_name = 'PulsepairVelocity' | |
|
|
232 | plot_type = 'scatter' | |
|
|
233 | buffering = False | |
| @@ -1,1409 +1,1557 | |||
|
|
1 | 1 | import sys |
|
|
2 | import numpy | |
|
|
2 | import numpy,math | |
|
|
3 | 3 | from scipy import interpolate |
|
|
4 | 4 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator |
|
|
5 | 5 | from schainpy.model.data.jrodata import Voltage |
|
|
6 | 6 | from schainpy.utils import log |
|
|
7 | 7 | from time import time |
|
|
8 | 8 | |
|
|
9 | 9 | |
|
|
10 | 10 | |
|
|
11 |
class VoltageProc(ProcessingUnit): |
|
|
|
12 | ||
|
|
11 | class VoltageProc(ProcessingUnit): | |
|
|
12 | ||
|
|
13 | 13 | def __init__(self): |
|
|
14 | 14 | |
|
|
15 | 15 | ProcessingUnit.__init__(self) |
|
|
16 | 16 | |
|
|
17 | 17 | self.dataOut = Voltage() |
|
|
18 | 18 | self.flip = 1 |
|
|
19 | 19 | self.setupReq = False |
|
|
20 | 20 | |
|
|
21 | 21 | def run(self): |
|
|
22 | 22 | |
|
|
23 | 23 | if self.dataIn.type == 'AMISR': |
|
|
24 | 24 | self.__updateObjFromAmisrInput() |
|
|
25 | 25 | |
|
|
26 | 26 | if self.dataIn.type == 'Voltage': |
|
|
27 | 27 | self.dataOut.copy(self.dataIn) |
|
|
28 | 28 | |
|
|
29 | 29 | def __updateObjFromAmisrInput(self): |
|
|
30 | 30 | |
|
|
31 | 31 | self.dataOut.timeZone = self.dataIn.timeZone |
|
|
32 | 32 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
|
33 | 33 | self.dataOut.errorCount = self.dataIn.errorCount |
|
|
34 | 34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
|
35 | 35 | |
|
|
36 | 36 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
|
37 | 37 | self.dataOut.data = self.dataIn.data |
|
|
38 | 38 | self.dataOut.utctime = self.dataIn.utctime |
|
|
39 | 39 | self.dataOut.channelList = self.dataIn.channelList |
|
|
40 | 40 | #self.dataOut.timeInterval = self.dataIn.timeInterval |
|
|
41 | 41 | self.dataOut.heightList = self.dataIn.heightList |
|
|
42 | 42 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
|
43 | 43 | |
|
|
44 | 44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
|
45 | 45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
|
46 | 46 | self.dataOut.frequency = self.dataIn.frequency |
|
|
47 | 47 | |
|
|
48 | 48 | self.dataOut.azimuth = self.dataIn.azimuth |
|
|
49 | 49 | self.dataOut.zenith = self.dataIn.zenith |
|
|
50 | 50 | |
|
|
51 | 51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
|
52 | 52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
|
53 | 53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
|
54 | ||
|
|
54 | ||
|
|
55 | 55 | |
|
|
56 | 56 | class selectChannels(Operation): |
|
|
57 | ||
|
|
57 | ||
|
|
58 | 58 | def run(self, dataOut, channelList): |
|
|
59 | 59 | |
|
|
60 | 60 | channelIndexList = [] |
|
|
61 | 61 | self.dataOut = dataOut |
|
|
62 | ||
|
|
63 | 62 | for channel in channelList: |
|
|
64 | 63 | if channel not in self.dataOut.channelList: |
|
|
65 | 64 | raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList))) |
|
|
66 | 65 | |
|
|
67 | 66 | index = self.dataOut.channelList.index(channel) |
|
|
68 | 67 | channelIndexList.append(index) |
|
|
69 | ||
|
|
70 | 68 | self.selectChannelsByIndex(channelIndexList) |
|
|
71 | 69 | return self.dataOut |
|
|
72 | 70 | |
|
|
73 | 71 | def selectChannelsByIndex(self, channelIndexList): |
|
|
74 | 72 | """ |
|
|
75 | 73 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
|
76 | 74 | |
|
|
77 | 75 | Input: |
|
|
78 | 76 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
|
79 | 77 | |
|
|
80 | 78 | Affected: |
|
|
81 | 79 | self.dataOut.data |
|
|
82 | 80 | self.dataOut.channelIndexList |
|
|
83 | 81 | self.dataOut.nChannels |
|
|
84 | 82 | self.dataOut.m_ProcessingHeader.totalSpectra |
|
|
85 | 83 | self.dataOut.systemHeaderObj.numChannels |
|
|
86 | 84 | self.dataOut.m_ProcessingHeader.blockSize |
|
|
87 | 85 | |
|
|
88 | 86 | Return: |
|
|
89 | 87 | None |
|
|
90 | 88 | """ |
|
|
91 | 89 | |
|
|
92 | 90 | for channelIndex in channelIndexList: |
|
|
93 | 91 | if channelIndex not in self.dataOut.channelIndexList: |
|
|
94 | 92 | raise ValueError("The value %d in channelIndexList is not valid" %channelIndex) |
|
|
95 | 93 | |
|
|
96 | 94 | if self.dataOut.type == 'Voltage': |
|
|
97 | 95 | if self.dataOut.flagDataAsBlock: |
|
|
98 | 96 | """ |
|
|
99 | 97 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
100 | 98 | """ |
|
|
101 | 99 | data = self.dataOut.data[channelIndexList,:,:] |
|
|
102 | 100 | else: |
|
|
103 | 101 | data = self.dataOut.data[channelIndexList,:] |
|
|
104 | 102 | |
|
|
105 | 103 | self.dataOut.data = data |
|
|
106 | 104 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
|
107 | 105 | self.dataOut.channelList = range(len(channelIndexList)) |
|
|
106 | ||
|
|
108 | 107 | elif self.dataOut.type == 'Spectra': |
|
|
109 | 108 | data_spc = self.dataOut.data_spc[channelIndexList, :] |
|
|
110 | 109 | data_dc = self.dataOut.data_dc[channelIndexList, :] |
|
|
111 | 110 | |
|
|
112 | 111 | self.dataOut.data_spc = data_spc |
|
|
113 | 112 | self.dataOut.data_dc = data_dc |
|
|
114 | 113 | |
|
|
115 | 114 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
|
116 | 115 | self.dataOut.channelList = range(len(channelIndexList)) |
|
|
117 | 116 | self.__selectPairsByChannel(channelIndexList) |
|
|
118 | 117 | |
|
|
119 | 118 | return 1 |
|
|
120 | 119 | |
|
|
121 | 120 | def __selectPairsByChannel(self, channelList=None): |
|
|
122 | 121 | |
|
|
123 | 122 | if channelList == None: |
|
|
124 | 123 | return |
|
|
125 | 124 | |
|
|
126 | 125 | pairsIndexListSelected = [] |
|
|
127 | 126 | for pairIndex in self.dataOut.pairsIndexList: |
|
|
128 | 127 | # First pair |
|
|
129 | 128 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
|
130 | 129 | continue |
|
|
131 | 130 | # Second pair |
|
|
132 | 131 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
|
133 | 132 | continue |
|
|
134 | 133 | |
|
|
135 | 134 | pairsIndexListSelected.append(pairIndex) |
|
|
136 | 135 | |
|
|
137 | 136 | if not pairsIndexListSelected: |
|
|
138 | 137 | self.dataOut.data_cspc = None |
|
|
139 | 138 | self.dataOut.pairsList = [] |
|
|
140 | 139 | return |
|
|
141 | 140 | |
|
|
142 | 141 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
|
143 | 142 | self.dataOut.pairsList = [self.dataOut.pairsList[i] |
|
|
144 | 143 | for i in pairsIndexListSelected] |
|
|
145 | 144 | |
|
|
146 | 145 | return |
|
|
147 | 146 | |
|
|
148 | 147 | class selectHeights(Operation): |
|
|
149 | ||
|
|
148 | ||
|
|
150 | 149 | def run(self, dataOut, minHei=None, maxHei=None): |
|
|
151 | 150 | """ |
|
|
152 | 151 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
|
153 | 152 | minHei <= height <= maxHei |
|
|
154 | 153 | |
|
|
155 | 154 | Input: |
|
|
156 | 155 | minHei : valor minimo de altura a considerar |
|
|
157 | 156 | maxHei : valor maximo de altura a considerar |
|
|
158 | 157 | |
|
|
159 | 158 | Affected: |
|
|
160 | 159 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
|
161 | 160 | |
|
|
162 | 161 | Return: |
|
|
163 | 162 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
164 | 163 | """ |
|
|
165 | 164 | |
|
|
166 | 165 | self.dataOut = dataOut |
|
|
167 | 166 | |
|
|
168 | 167 | if minHei == None: |
|
|
169 | 168 | minHei = self.dataOut.heightList[0] |
|
|
170 | 169 | |
|
|
171 | 170 | if maxHei == None: |
|
|
172 | 171 | maxHei = self.dataOut.heightList[-1] |
|
|
173 | 172 | |
|
|
174 | 173 | if (minHei < self.dataOut.heightList[0]): |
|
|
175 | 174 | minHei = self.dataOut.heightList[0] |
|
|
176 | 175 | |
|
|
177 | 176 | if (maxHei > self.dataOut.heightList[-1]): |
|
|
178 | 177 | maxHei = self.dataOut.heightList[-1] |
|
|
179 | 178 | |
|
|
180 | 179 | minIndex = 0 |
|
|
181 | 180 | maxIndex = 0 |
|
|
182 | 181 | heights = self.dataOut.heightList |
|
|
183 | 182 | |
|
|
184 | 183 | inda = numpy.where(heights >= minHei) |
|
|
185 | 184 | indb = numpy.where(heights <= maxHei) |
|
|
186 | 185 | |
|
|
187 | 186 | try: |
|
|
188 | 187 | minIndex = inda[0][0] |
|
|
189 | 188 | except: |
|
|
190 | 189 | minIndex = 0 |
|
|
191 | 190 | |
|
|
192 | 191 | try: |
|
|
193 | 192 | maxIndex = indb[0][-1] |
|
|
194 | 193 | except: |
|
|
195 | 194 | maxIndex = len(heights) |
|
|
196 | 195 | |
|
|
197 | 196 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
|
198 | 197 | |
|
|
199 | 198 | return self.dataOut |
|
|
200 | 199 | |
|
|
201 | 200 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
|
202 | 201 | """ |
|
|
203 | 202 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
|
204 | 203 | minIndex <= index <= maxIndex |
|
|
205 | 204 | |
|
|
206 | 205 | Input: |
|
|
207 | 206 | minIndex : valor de indice minimo de altura a considerar |
|
|
208 | 207 | maxIndex : valor de indice maximo de altura a considerar |
|
|
209 | 208 | |
|
|
210 | 209 | Affected: |
|
|
211 | 210 | self.dataOut.data |
|
|
212 | 211 | self.dataOut.heightList |
|
|
213 | 212 | |
|
|
214 | 213 | Return: |
|
|
215 | 214 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
216 | 215 | """ |
|
|
217 | 216 | |
|
|
218 | 217 | if self.dataOut.type == 'Voltage': |
|
|
219 | 218 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
220 | 219 | raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
|
221 | 220 | |
|
|
222 | 221 | if (maxIndex >= self.dataOut.nHeights): |
|
|
223 | 222 | maxIndex = self.dataOut.nHeights |
|
|
224 | 223 | |
|
|
225 | 224 | #voltage |
|
|
226 | 225 | if self.dataOut.flagDataAsBlock: |
|
|
227 | 226 | """ |
|
|
228 | 227 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
229 | 228 | """ |
|
|
230 | 229 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
|
231 | 230 | else: |
|
|
232 | 231 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
|
233 | 232 | |
|
|
234 | 233 | # firstHeight = self.dataOut.heightList[minIndex] |
|
|
235 | 234 | |
|
|
236 | 235 | self.dataOut.data = data |
|
|
237 | 236 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
|
238 | 237 | |
|
|
239 | 238 | if self.dataOut.nHeights <= 1: |
|
|
240 | 239 | raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)) |
|
|
241 | 240 | elif self.dataOut.type == 'Spectra': |
|
|
242 | 241 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
243 | 242 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % ( |
|
|
244 | 243 | minIndex, maxIndex)) |
|
|
245 | 244 | |
|
|
246 | 245 | if (maxIndex >= self.dataOut.nHeights): |
|
|
247 | 246 | maxIndex = self.dataOut.nHeights - 1 |
|
|
248 | 247 | |
|
|
249 | 248 | # Spectra |
|
|
250 | 249 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
|
251 | 250 | |
|
|
252 | 251 | data_cspc = None |
|
|
253 | 252 | if self.dataOut.data_cspc is not None: |
|
|
254 | 253 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
|
255 | 254 | |
|
|
256 | 255 | data_dc = None |
|
|
257 | 256 | if self.dataOut.data_dc is not None: |
|
|
258 | 257 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
|
|
259 | 258 | |
|
|
260 | 259 | self.dataOut.data_spc = data_spc |
|
|
261 | 260 | self.dataOut.data_cspc = data_cspc |
|
|
262 | 261 | self.dataOut.data_dc = data_dc |
|
|
263 | 262 | |
|
|
264 | 263 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
|
|
265 | ||
|
|
264 | ||
|
|
266 | 265 | return 1 |
|
|
267 | 266 | |
|
|
268 | 267 | |
|
|
269 | 268 | class filterByHeights(Operation): |
|
|
270 | 269 | |
|
|
271 | 270 | def run(self, dataOut, window): |
|
|
272 | 271 | |
|
|
273 | 272 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
274 | 273 | |
|
|
275 | 274 | if window == None: |
|
|
276 | 275 | window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
|
277 | 276 | |
|
|
278 | 277 | newdelta = deltaHeight * window |
|
|
279 | 278 | r = dataOut.nHeights % window |
|
|
280 | 279 | newheights = (dataOut.nHeights-r)/window |
|
|
281 | 280 | |
|
|
282 | 281 | if newheights <= 1: |
|
|
283 | 282 | raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window)) |
|
|
284 | 283 | |
|
|
285 | 284 | if dataOut.flagDataAsBlock: |
|
|
286 | 285 | """ |
|
|
287 | 286 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
288 | 287 | """ |
|
|
289 |
buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)] |
|
|
|
288 | buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)] | |
|
|
290 | 289 | buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window) |
|
|
291 | 290 | buffer = numpy.sum(buffer,3) |
|
|
292 | 291 | |
|
|
293 | 292 | else: |
|
|
294 | 293 | buffer = dataOut.data[:,0:int(dataOut.nHeights-r)] |
|
|
295 | 294 | buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window)) |
|
|
296 | 295 | buffer = numpy.sum(buffer,2) |
|
|
297 | 296 | |
|
|
298 | 297 | dataOut.data = buffer |
|
|
299 | 298 | dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta |
|
|
300 | 299 | dataOut.windowOfFilter = window |
|
|
301 | 300 | |
|
|
302 | 301 | return dataOut |
|
|
303 | 302 | |
|
|
304 | 303 | |
|
|
305 | 304 | class setH0(Operation): |
|
|
306 | 305 | |
|
|
307 | 306 | def run(self, dataOut, h0, deltaHeight = None): |
|
|
308 | 307 | |
|
|
309 | 308 | if not deltaHeight: |
|
|
310 | 309 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
311 | 310 | |
|
|
312 | 311 | nHeights = dataOut.nHeights |
|
|
313 | 312 | |
|
|
314 | 313 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
|
315 | 314 | |
|
|
316 | 315 | dataOut.heightList = newHeiRange |
|
|
317 | 316 | |
|
|
318 | 317 | return dataOut |
|
|
319 | 318 | |
|
|
320 | 319 | |
|
|
321 | 320 | class deFlip(Operation): |
|
|
322 | 321 | |
|
|
323 | 322 | def run(self, dataOut, channelList = []): |
|
|
324 | 323 | |
|
|
325 | 324 | data = dataOut.data.copy() |
|
|
326 | 325 | |
|
|
327 | 326 | if dataOut.flagDataAsBlock: |
|
|
328 | 327 | flip = self.flip |
|
|
329 | 328 | profileList = list(range(dataOut.nProfiles)) |
|
|
330 | 329 | |
|
|
331 | 330 | if not channelList: |
|
|
332 | 331 | for thisProfile in profileList: |
|
|
333 | 332 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
|
334 | 333 | flip *= -1.0 |
|
|
335 | 334 | else: |
|
|
336 | 335 | for thisChannel in channelList: |
|
|
337 | 336 | if thisChannel not in dataOut.channelList: |
|
|
338 | 337 | continue |
|
|
339 | 338 | |
|
|
340 | 339 | for thisProfile in profileList: |
|
|
341 | 340 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
|
342 | 341 | flip *= -1.0 |
|
|
343 | 342 | |
|
|
344 | 343 | self.flip = flip |
|
|
345 | 344 | |
|
|
346 | 345 | else: |
|
|
347 | 346 | if not channelList: |
|
|
348 | 347 | data[:,:] = data[:,:]*self.flip |
|
|
349 | 348 | else: |
|
|
350 | 349 | for thisChannel in channelList: |
|
|
351 | 350 | if thisChannel not in dataOut.channelList: |
|
|
352 | 351 | continue |
|
|
353 | 352 | |
|
|
354 | 353 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
|
355 | 354 | |
|
|
356 | 355 | self.flip *= -1. |
|
|
357 | 356 | |
|
|
358 | 357 | dataOut.data = data |
|
|
359 | 358 | |
|
|
360 | 359 | return dataOut |
|
|
361 | 360 | |
|
|
362 | 361 | |
|
|
363 | 362 | class setAttribute(Operation): |
|
|
364 | 363 | ''' |
|
|
365 | 364 | Set an arbitrary attribute(s) to dataOut |
|
|
366 | 365 | ''' |
|
|
367 | 366 | |
|
|
368 | 367 | def __init__(self): |
|
|
369 | 368 | |
|
|
370 | 369 | Operation.__init__(self) |
|
|
371 | 370 | self._ready = False |
|
|
372 | 371 | |
|
|
373 | 372 | def run(self, dataOut, **kwargs): |
|
|
374 | 373 | |
|
|
375 | 374 | for key, value in kwargs.items(): |
|
|
376 | 375 | setattr(dataOut, key, value) |
|
|
377 | 376 | |
|
|
378 | 377 | return dataOut |
|
|
379 | 378 | |
|
|
380 | 379 | |
|
|
381 | 380 | class interpolateHeights(Operation): |
|
|
382 | 381 | |
|
|
383 | 382 | def run(self, dataOut, topLim, botLim): |
|
|
384 | 383 | #69 al 72 para julia |
|
|
385 | 384 | #82-84 para meteoros |
|
|
386 | 385 | if len(numpy.shape(dataOut.data))==2: |
|
|
387 | 386 | sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2 |
|
|
388 | 387 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
|
389 | 388 | #dataOut.data[:,botLim:limSup+1] = sampInterp |
|
|
390 | 389 | dataOut.data[:,botLim:topLim+1] = sampInterp |
|
|
391 | 390 | else: |
|
|
392 | 391 | nHeights = dataOut.data.shape[2] |
|
|
393 | 392 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
|
394 | 393 | y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))] |
|
|
395 | 394 | f = interpolate.interp1d(x, y, axis = 2) |
|
|
396 | 395 | xnew = numpy.arange(botLim,topLim+1) |
|
|
397 | 396 | ynew = f(xnew) |
|
|
398 | 397 | dataOut.data[:,:,botLim:topLim+1] = ynew |
|
|
399 | 398 | |
|
|
400 | 399 | return dataOut |
|
|
401 | 400 | |
|
|
402 | 401 | |
|
|
403 | 402 | class CohInt(Operation): |
|
|
404 | 403 | |
|
|
405 | 404 | isConfig = False |
|
|
406 | 405 | __profIndex = 0 |
|
|
407 | 406 | __byTime = False |
|
|
408 | 407 | __initime = None |
|
|
409 | 408 | __lastdatatime = None |
|
|
410 | 409 | __integrationtime = None |
|
|
411 | 410 | __buffer = None |
|
|
412 | 411 | __bufferStride = [] |
|
|
413 | 412 | __dataReady = False |
|
|
414 | 413 | __profIndexStride = 0 |
|
|
415 | 414 | __dataToPutStride = False |
|
|
416 | 415 | n = None |
|
|
417 | 416 | |
|
|
418 | 417 | def __init__(self, **kwargs): |
|
|
419 | 418 | |
|
|
420 | 419 | Operation.__init__(self, **kwargs) |
|
|
421 | 420 | |
|
|
422 | 421 | # self.isConfig = False |
|
|
423 | 422 | |
|
|
424 | 423 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): |
|
|
425 | 424 | """ |
|
|
426 | 425 | Set the parameters of the integration class. |
|
|
427 | 426 | |
|
|
428 | 427 | Inputs: |
|
|
429 | 428 | |
|
|
430 | 429 | n : Number of coherent integrations |
|
|
431 | 430 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
|
432 | 431 | overlapping : |
|
|
433 | 432 | """ |
|
|
434 | 433 | |
|
|
435 | 434 | self.__initime = None |
|
|
436 | 435 | self.__lastdatatime = 0 |
|
|
437 | 436 | self.__buffer = None |
|
|
438 | 437 | self.__dataReady = False |
|
|
439 | 438 | self.byblock = byblock |
|
|
440 | 439 | self.stride = stride |
|
|
441 | 440 | |
|
|
442 | 441 | if n == None and timeInterval == None: |
|
|
443 | 442 | raise ValueError("n or timeInterval should be specified ...") |
|
|
444 | 443 | |
|
|
445 | 444 | if n != None: |
|
|
446 | 445 | self.n = n |
|
|
447 | 446 | self.__byTime = False |
|
|
448 | 447 | else: |
|
|
449 | 448 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
|
450 | 449 | self.n = 9999 |
|
|
451 | 450 | self.__byTime = True |
|
|
452 | 451 | |
|
|
453 | 452 | if overlapping: |
|
|
454 | 453 | self.__withOverlapping = True |
|
|
455 | 454 | self.__buffer = None |
|
|
456 | 455 | else: |
|
|
457 | 456 | self.__withOverlapping = False |
|
|
458 | 457 | self.__buffer = 0 |
|
|
459 | 458 | |
|
|
460 | 459 | self.__profIndex = 0 |
|
|
461 | 460 | |
|
|
462 | 461 | def putData(self, data): |
|
|
463 | 462 | |
|
|
464 | 463 | """ |
|
|
465 | 464 | Add a profile to the __buffer and increase in one the __profileIndex |
|
|
466 | 465 | |
|
|
467 | 466 | """ |
|
|
468 | 467 | |
|
|
469 | 468 | if not self.__withOverlapping: |
|
|
470 | 469 | self.__buffer += data.copy() |
|
|
471 | 470 | self.__profIndex += 1 |
|
|
472 | 471 | return |
|
|
473 | 472 | |
|
|
474 | 473 | #Overlapping data |
|
|
475 | 474 | nChannels, nHeis = data.shape |
|
|
476 | 475 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
|
477 | 476 | |
|
|
478 | 477 | #If the buffer is empty then it takes the data value |
|
|
479 | 478 | if self.__buffer is None: |
|
|
480 | 479 | self.__buffer = data |
|
|
481 | 480 | self.__profIndex += 1 |
|
|
482 | 481 | return |
|
|
483 | 482 | |
|
|
484 | 483 | #If the buffer length is lower than n then stakcing the data value |
|
|
485 | 484 | if self.__profIndex < self.n: |
|
|
486 | 485 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
|
487 | 486 | self.__profIndex += 1 |
|
|
488 | 487 | return |
|
|
489 | 488 | |
|
|
490 | 489 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
|
491 | 490 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
|
492 | 491 | self.__buffer[self.n-1] = data |
|
|
493 | 492 | self.__profIndex = self.n |
|
|
494 | 493 | return |
|
|
495 | 494 | |
|
|
496 | 495 | |
|
|
497 | 496 | def pushData(self): |
|
|
498 | 497 | """ |
|
|
499 | 498 | Return the sum of the last profiles and the profiles used in the sum. |
|
|
500 | 499 | |
|
|
501 | 500 | Affected: |
|
|
502 | 501 | |
|
|
503 | 502 | self.__profileIndex |
|
|
504 | 503 | |
|
|
505 | 504 | """ |
|
|
506 | 505 | |
|
|
507 | 506 | if not self.__withOverlapping: |
|
|
508 | 507 | data = self.__buffer |
|
|
509 | 508 | n = self.__profIndex |
|
|
510 | 509 | |
|
|
511 | 510 | self.__buffer = 0 |
|
|
512 | 511 | self.__profIndex = 0 |
|
|
513 | 512 | |
|
|
514 | 513 | return data, n |
|
|
515 | 514 | |
|
|
516 | 515 | #Integration with Overlapping |
|
|
517 | 516 | data = numpy.sum(self.__buffer, axis=0) |
|
|
518 | 517 | # print data |
|
|
519 | 518 | # raise |
|
|
520 | 519 | n = self.__profIndex |
|
|
521 | 520 | |
|
|
522 | 521 | return data, n |
|
|
523 | 522 | |
|
|
524 | 523 | def byProfiles(self, data): |
|
|
525 | 524 | |
|
|
526 | 525 | self.__dataReady = False |
|
|
527 | 526 | avgdata = None |
|
|
528 | 527 | # n = None |
|
|
529 | 528 | # print data |
|
|
530 | 529 | # raise |
|
|
531 | 530 | self.putData(data) |
|
|
532 | 531 | |
|
|
533 | 532 | if self.__profIndex == self.n: |
|
|
534 | 533 | avgdata, n = self.pushData() |
|
|
535 | 534 | self.__dataReady = True |
|
|
536 | 535 | |
|
|
537 | 536 | return avgdata |
|
|
538 | 537 | |
|
|
539 | 538 | def byTime(self, data, datatime): |
|
|
540 | 539 | |
|
|
541 | 540 | self.__dataReady = False |
|
|
542 | 541 | avgdata = None |
|
|
543 | 542 | n = None |
|
|
544 | 543 | |
|
|
545 | 544 | self.putData(data) |
|
|
546 | 545 | |
|
|
547 | 546 | if (datatime - self.__initime) >= self.__integrationtime: |
|
|
548 | 547 | avgdata, n = self.pushData() |
|
|
549 | 548 | self.n = n |
|
|
550 | 549 | self.__dataReady = True |
|
|
551 | 550 | |
|
|
552 | 551 | return avgdata |
|
|
553 | 552 | |
|
|
554 | 553 | def integrateByStride(self, data, datatime): |
|
|
555 | 554 | # print data |
|
|
556 | 555 | if self.__profIndex == 0: |
|
|
557 | 556 | self.__buffer = [[data.copy(), datatime]] |
|
|
558 | 557 | else: |
|
|
559 | 558 | self.__buffer.append([data.copy(),datatime]) |
|
|
560 | 559 | self.__profIndex += 1 |
|
|
561 | 560 | self.__dataReady = False |
|
|
562 | 561 | |
|
|
563 | 562 | if self.__profIndex == self.n * self.stride : |
|
|
564 | 563 | self.__dataToPutStride = True |
|
|
565 | 564 | self.__profIndexStride = 0 |
|
|
566 | 565 | self.__profIndex = 0 |
|
|
567 | 566 | self.__bufferStride = [] |
|
|
568 | 567 | for i in range(self.stride): |
|
|
569 | 568 | current = self.__buffer[i::self.stride] |
|
|
570 | 569 | data = numpy.sum([t[0] for t in current], axis=0) |
|
|
571 | 570 | avgdatatime = numpy.average([t[1] for t in current]) |
|
|
572 | 571 | # print data |
|
|
573 | 572 | self.__bufferStride.append((data, avgdatatime)) |
|
|
574 | 573 | |
|
|
575 | 574 | if self.__dataToPutStride: |
|
|
576 | 575 | self.__dataReady = True |
|
|
577 | 576 | self.__profIndexStride += 1 |
|
|
578 | 577 | if self.__profIndexStride == self.stride: |
|
|
579 | 578 | self.__dataToPutStride = False |
|
|
580 | 579 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
|
581 | 580 | # raise |
|
|
582 | 581 | return self.__bufferStride[self.__profIndexStride - 1] |
|
|
583 | ||
|
|
584 | ||
|
|
582 | ||
|
|
583 | ||
|
|
585 | 584 | return None, None |
|
|
586 | 585 | |
|
|
587 | 586 | def integrate(self, data, datatime=None): |
|
|
588 | 587 | |
|
|
589 | 588 | if self.__initime == None: |
|
|
590 | 589 | self.__initime = datatime |
|
|
591 | 590 | |
|
|
592 | 591 | if self.__byTime: |
|
|
593 | 592 | avgdata = self.byTime(data, datatime) |
|
|
594 | 593 | else: |
|
|
595 | 594 | avgdata = self.byProfiles(data) |
|
|
596 | 595 | |
|
|
597 | 596 | |
|
|
598 | 597 | self.__lastdatatime = datatime |
|
|
599 | 598 | |
|
|
600 | 599 | if avgdata is None: |
|
|
601 | 600 | return None, None |
|
|
602 | 601 | |
|
|
603 | 602 | avgdatatime = self.__initime |
|
|
604 | 603 | |
|
|
605 | 604 | deltatime = datatime - self.__lastdatatime |
|
|
606 | ||
|
|
605 | ||
|
|
607 | 606 | if not self.__withOverlapping: |
|
|
608 | 607 | self.__initime = datatime |
|
|
609 | 608 | else: |
|
|
610 | 609 | self.__initime += deltatime |
|
|
611 | 610 | |
|
|
612 | 611 | return avgdata, avgdatatime |
|
|
613 | 612 | |
|
|
614 | 613 | def integrateByBlock(self, dataOut): |
|
|
615 | 614 | |
|
|
616 | 615 | times = int(dataOut.data.shape[1]/self.n) |
|
|
617 | 616 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
|
618 | 617 | |
|
|
619 | 618 | id_min = 0 |
|
|
620 | 619 | id_max = self.n |
|
|
621 | 620 | |
|
|
622 | 621 | for i in range(times): |
|
|
623 | 622 | junk = dataOut.data[:,id_min:id_max,:] |
|
|
624 | 623 | avgdata[:,i,:] = junk.sum(axis=1) |
|
|
625 | 624 | id_min += self.n |
|
|
626 | 625 | id_max += self.n |
|
|
627 | 626 | |
|
|
628 | 627 | timeInterval = dataOut.ippSeconds*self.n |
|
|
629 | 628 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
|
630 | 629 | self.__dataReady = True |
|
|
631 | 630 | return avgdata, avgdatatime |
|
|
632 | ||
|
|
631 | ||
|
|
633 | 632 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): |
|
|
634 | 633 | |
|
|
635 | 634 | if not self.isConfig: |
|
|
636 | 635 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) |
|
|
637 | 636 | self.isConfig = True |
|
|
638 | 637 | |
|
|
639 | 638 | if dataOut.flagDataAsBlock: |
|
|
640 | 639 | """ |
|
|
641 | 640 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
642 | 641 | """ |
|
|
643 | 642 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
|
644 | 643 | dataOut.nProfiles /= self.n |
|
|
645 | 644 | else: |
|
|
646 |
if stride is None: |
|
|
|
645 | if stride is None: | |
|
|
647 | 646 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
|
648 | 647 | else: |
|
|
649 | 648 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
|
650 | 649 | |
|
|
651 | ||
|
|
650 | ||
|
|
652 | 651 | # dataOut.timeInterval *= n |
|
|
653 | 652 | dataOut.flagNoData = True |
|
|
654 | 653 | |
|
|
655 | 654 | if self.__dataReady: |
|
|
656 | 655 | dataOut.data = avgdata |
|
|
657 | 656 | dataOut.nCohInt *= self.n |
|
|
658 | 657 | dataOut.utctime = avgdatatime |
|
|
659 | 658 | # print avgdata, avgdatatime |
|
|
660 | 659 | # raise |
|
|
661 | 660 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
|
662 | 661 | dataOut.flagNoData = False |
|
|
663 | 662 | return dataOut |
|
|
664 | 663 | |
|
|
665 | 664 | class Decoder(Operation): |
|
|
666 | 665 | |
|
|
667 | 666 | isConfig = False |
|
|
668 | 667 | __profIndex = 0 |
|
|
669 | 668 | |
|
|
670 | 669 | code = None |
|
|
671 | 670 | |
|
|
672 | 671 | nCode = None |
|
|
673 | 672 | nBaud = None |
|
|
674 | 673 | |
|
|
675 | 674 | def __init__(self, **kwargs): |
|
|
676 | 675 | |
|
|
677 | 676 | Operation.__init__(self, **kwargs) |
|
|
678 | 677 | |
|
|
679 | 678 | self.times = None |
|
|
680 | 679 | self.osamp = None |
|
|
681 | 680 | # self.__setValues = False |
|
|
682 | 681 | self.isConfig = False |
|
|
683 | 682 | self.setupReq = False |
|
|
684 | 683 | def setup(self, code, osamp, dataOut): |
|
|
685 | 684 | |
|
|
686 | 685 | self.__profIndex = 0 |
|
|
687 | 686 | |
|
|
688 | 687 | self.code = code |
|
|
689 | 688 | |
|
|
690 | 689 | self.nCode = len(code) |
|
|
691 | 690 | self.nBaud = len(code[0]) |
|
|
692 | 691 | |
|
|
693 | 692 | if (osamp != None) and (osamp >1): |
|
|
694 | 693 | self.osamp = osamp |
|
|
695 | 694 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
|
696 | 695 | self.nBaud = self.nBaud*self.osamp |
|
|
697 | 696 | |
|
|
698 | 697 | self.__nChannels = dataOut.nChannels |
|
|
699 | 698 | self.__nProfiles = dataOut.nProfiles |
|
|
700 | 699 | self.__nHeis = dataOut.nHeights |
|
|
701 | 700 | |
|
|
702 | 701 | if self.__nHeis < self.nBaud: |
|
|
703 | 702 | raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud)) |
|
|
704 | 703 | |
|
|
705 | 704 | #Frequency |
|
|
706 | 705 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
|
707 | 706 | |
|
|
708 | 707 | __codeBuffer[:,0:self.nBaud] = self.code |
|
|
709 | 708 | |
|
|
710 | 709 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
|
711 | 710 | |
|
|
712 | 711 | if dataOut.flagDataAsBlock: |
|
|
713 | 712 | |
|
|
714 | 713 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
|
715 | 714 | |
|
|
716 | 715 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
|
717 | 716 | |
|
|
718 | 717 | else: |
|
|
719 | 718 | |
|
|
720 | 719 | #Time |
|
|
721 | 720 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
|
722 | 721 | |
|
|
723 | 722 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
|
724 | 723 | |
|
|
725 | 724 | def __convolutionInFreq(self, data): |
|
|
726 | 725 | |
|
|
727 | 726 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
728 | 727 | |
|
|
729 | 728 | fft_data = numpy.fft.fft(data, axis=1) |
|
|
730 | 729 | |
|
|
731 | 730 | conv = fft_data*fft_code |
|
|
732 | 731 | |
|
|
733 | 732 | data = numpy.fft.ifft(conv,axis=1) |
|
|
734 | 733 | |
|
|
735 | 734 | return data |
|
|
736 | 735 | |
|
|
737 | 736 | def __convolutionInFreqOpt(self, data): |
|
|
738 | 737 | |
|
|
739 | 738 | raise NotImplementedError |
|
|
740 | 739 | |
|
|
741 | 740 | def __convolutionInTime(self, data): |
|
|
742 | 741 | |
|
|
743 | 742 | code = self.code[self.__profIndex] |
|
|
744 | 743 | for i in range(self.__nChannels): |
|
|
745 | 744 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] |
|
|
746 | 745 | |
|
|
747 | 746 | return self.datadecTime |
|
|
748 | 747 | |
|
|
749 | 748 | def __convolutionByBlockInTime(self, data): |
|
|
750 | 749 | |
|
|
751 | 750 | repetitions = int(self.__nProfiles / self.nCode) |
|
|
752 | 751 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) |
|
|
753 | 752 | junk = junk.flatten() |
|
|
754 | 753 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
|
755 | 754 | profilesList = range(self.__nProfiles) |
|
|
756 | ||
|
|
757 |
for i in range(self.__nChannels): |
|
|
|
758 |
for j in profilesList: |
|
|
|
759 |
self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] |
|
|
|
760 |
return self.datadecTime |
|
|
|
755 | ||
|
|
756 | for i in range(self.__nChannels): | |
|
|
757 | for j in profilesList: | |
|
|
758 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] | |
|
|
759 | return self.datadecTime | |
|
|
761 | 760 | |
|
|
762 | 761 | def __convolutionByBlockInFreq(self, data): |
|
|
763 | 762 | |
|
|
764 | 763 | raise NotImplementedError("Decoder by frequency fro Blocks not implemented") |
|
|
765 | 764 | |
|
|
766 | 765 | |
|
|
767 | 766 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
768 | 767 | |
|
|
769 | 768 | fft_data = numpy.fft.fft(data, axis=2) |
|
|
770 | 769 | |
|
|
771 | 770 | conv = fft_data*fft_code |
|
|
772 | 771 | |
|
|
773 | 772 | data = numpy.fft.ifft(conv,axis=2) |
|
|
774 | 773 | |
|
|
775 | 774 | return data |
|
|
776 | 775 | |
|
|
777 | ||
|
|
776 | ||
|
|
778 | 777 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): |
|
|
779 | 778 | |
|
|
780 | 779 | if dataOut.flagDecodeData: |
|
|
781 | 780 | print("This data is already decoded, recoding again ...") |
|
|
782 | 781 | |
|
|
783 | 782 | if not self.isConfig: |
|
|
784 | 783 | |
|
|
785 | 784 | if code is None: |
|
|
786 | 785 | if dataOut.code is None: |
|
|
787 | 786 | raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type) |
|
|
788 | 787 | |
|
|
789 | 788 | code = dataOut.code |
|
|
790 | 789 | else: |
|
|
791 | 790 | code = numpy.array(code).reshape(nCode,nBaud) |
|
|
792 | 791 | self.setup(code, osamp, dataOut) |
|
|
793 | 792 | |
|
|
794 | 793 | self.isConfig = True |
|
|
795 | 794 | |
|
|
796 | 795 | if mode == 3: |
|
|
797 | 796 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) |
|
|
798 | 797 | |
|
|
799 | 798 | if times != None: |
|
|
800 | 799 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") |
|
|
801 | 800 | |
|
|
802 | 801 | if self.code is None: |
|
|
803 | 802 | print("Fail decoding: Code is not defined.") |
|
|
804 | 803 | return |
|
|
805 | 804 | |
|
|
806 | 805 | self.__nProfiles = dataOut.nProfiles |
|
|
807 | 806 | datadec = None |
|
|
808 | ||
|
|
807 | ||
|
|
809 | 808 | if mode == 3: |
|
|
810 | 809 | mode = 0 |
|
|
811 | 810 | |
|
|
812 | 811 | if dataOut.flagDataAsBlock: |
|
|
813 | 812 | """ |
|
|
814 | 813 | Decoding when data have been read as block, |
|
|
815 | 814 | """ |
|
|
816 | 815 | |
|
|
817 | 816 | if mode == 0: |
|
|
818 | 817 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
|
819 | 818 | if mode == 1: |
|
|
820 | 819 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
|
821 | 820 | else: |
|
|
822 | 821 | """ |
|
|
823 | 822 | Decoding when data have been read profile by profile |
|
|
824 | 823 | """ |
|
|
825 | 824 | if mode == 0: |
|
|
826 | 825 | datadec = self.__convolutionInTime(dataOut.data) |
|
|
827 | 826 | |
|
|
828 | 827 | if mode == 1: |
|
|
829 | 828 | datadec = self.__convolutionInFreq(dataOut.data) |
|
|
830 | 829 | |
|
|
831 | 830 | if mode == 2: |
|
|
832 | 831 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
|
833 | 832 | |
|
|
834 | 833 | if datadec is None: |
|
|
835 | 834 | raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode) |
|
|
836 | 835 | |
|
|
837 | 836 | dataOut.code = self.code |
|
|
838 | 837 | dataOut.nCode = self.nCode |
|
|
839 | 838 | dataOut.nBaud = self.nBaud |
|
|
840 | 839 | |
|
|
841 | 840 | dataOut.data = datadec |
|
|
842 | 841 | |
|
|
843 | 842 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
|
844 | 843 | |
|
|
845 | 844 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
|
846 | 845 | |
|
|
847 | 846 | if self.__profIndex == self.nCode-1: |
|
|
848 | 847 | self.__profIndex = 0 |
|
|
849 | 848 | return dataOut |
|
|
850 | 849 | |
|
|
851 | 850 | self.__profIndex += 1 |
|
|
852 | 851 | |
|
|
853 | 852 | return dataOut |
|
|
854 | 853 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
|
855 | 854 | |
|
|
856 | 855 | |
|
|
857 | 856 | class ProfileConcat(Operation): |
|
|
858 | 857 | |
|
|
859 | 858 | isConfig = False |
|
|
860 | 859 | buffer = None |
|
|
861 | 860 | |
|
|
862 | 861 | def __init__(self, **kwargs): |
|
|
863 | 862 | |
|
|
864 | 863 | Operation.__init__(self, **kwargs) |
|
|
865 | 864 | self.profileIndex = 0 |
|
|
866 | 865 | |
|
|
867 | 866 | def reset(self): |
|
|
868 | 867 | self.buffer = numpy.zeros_like(self.buffer) |
|
|
869 | 868 | self.start_index = 0 |
|
|
870 | 869 | self.times = 1 |
|
|
871 | 870 | |
|
|
872 | 871 | def setup(self, data, m, n=1): |
|
|
873 | 872 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
|
874 | 873 | self.nHeights = data.shape[1]#.nHeights |
|
|
875 | 874 | self.start_index = 0 |
|
|
876 | 875 | self.times = 1 |
|
|
877 | 876 | |
|
|
878 | 877 | def concat(self, data): |
|
|
879 | 878 | |
|
|
880 | 879 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
|
881 | 880 | self.start_index = self.start_index + self.nHeights |
|
|
882 | 881 | |
|
|
883 | 882 | def run(self, dataOut, m): |
|
|
884 | 883 | dataOut.flagNoData = True |
|
|
885 | 884 | |
|
|
886 | 885 | if not self.isConfig: |
|
|
887 | 886 | self.setup(dataOut.data, m, 1) |
|
|
888 | 887 | self.isConfig = True |
|
|
889 | 888 | |
|
|
890 | 889 | if dataOut.flagDataAsBlock: |
|
|
891 | 890 | raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False") |
|
|
892 | 891 | |
|
|
893 | 892 | else: |
|
|
894 | 893 | self.concat(dataOut.data) |
|
|
895 | 894 | self.times += 1 |
|
|
896 | 895 | if self.times > m: |
|
|
897 | 896 | dataOut.data = self.buffer |
|
|
898 | 897 | self.reset() |
|
|
899 | 898 | dataOut.flagNoData = False |
|
|
900 | 899 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
|
901 | 900 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
902 | 901 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
|
903 | 902 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
|
904 | 903 | dataOut.ippSeconds *= m |
|
|
905 | 904 | return dataOut |
|
|
906 | 905 | |
|
|
907 | 906 | class ProfileSelector(Operation): |
|
|
908 | 907 | |
|
|
909 | 908 | profileIndex = None |
|
|
910 | 909 | # Tamanho total de los perfiles |
|
|
911 | 910 | nProfiles = None |
|
|
912 | 911 | |
|
|
913 | 912 | def __init__(self, **kwargs): |
|
|
914 | 913 | |
|
|
915 | 914 | Operation.__init__(self, **kwargs) |
|
|
916 | 915 | self.profileIndex = 0 |
|
|
917 | 916 | |
|
|
918 | 917 | def incProfileIndex(self): |
|
|
919 | 918 | |
|
|
920 | 919 | self.profileIndex += 1 |
|
|
921 | 920 | |
|
|
922 | 921 | if self.profileIndex >= self.nProfiles: |
|
|
923 | 922 | self.profileIndex = 0 |
|
|
924 | 923 | |
|
|
925 | 924 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
|
926 | 925 | |
|
|
927 | 926 | if profileIndex < minIndex: |
|
|
928 | 927 | return False |
|
|
929 | 928 | |
|
|
930 | 929 | if profileIndex > maxIndex: |
|
|
931 | 930 | return False |
|
|
932 | 931 | |
|
|
933 | 932 | return True |
|
|
934 | 933 | |
|
|
935 | 934 | def isThisProfileInList(self, profileIndex, profileList): |
|
|
936 | 935 | |
|
|
937 | 936 | if profileIndex not in profileList: |
|
|
938 | 937 | return False |
|
|
939 | 938 | |
|
|
940 | 939 | return True |
|
|
941 | 940 | |
|
|
942 | 941 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
|
943 | 942 | |
|
|
944 | 943 | """ |
|
|
945 | 944 | ProfileSelector: |
|
|
946 | 945 | |
|
|
947 | 946 | Inputs: |
|
|
948 | 947 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
|
949 | 948 | |
|
|
950 | 949 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
|
951 | 950 | |
|
|
952 | 951 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
|
953 | 952 | |
|
|
954 | 953 | """ |
|
|
955 | 954 | |
|
|
956 | 955 | if rangeList is not None: |
|
|
957 | 956 | if type(rangeList[0]) not in (tuple, list): |
|
|
958 | 957 | rangeList = [rangeList] |
|
|
959 | 958 | |
|
|
960 | 959 | dataOut.flagNoData = True |
|
|
961 | 960 | |
|
|
962 | 961 | if dataOut.flagDataAsBlock: |
|
|
963 | 962 | """ |
|
|
964 | 963 | data dimension = [nChannels, nProfiles, nHeis] |
|
|
965 | 964 | """ |
|
|
966 | 965 | if profileList != None: |
|
|
967 | 966 | dataOut.data = dataOut.data[:,profileList,:] |
|
|
968 | 967 | |
|
|
969 | 968 | if profileRangeList != None: |
|
|
970 | 969 | minIndex = profileRangeList[0] |
|
|
971 | 970 | maxIndex = profileRangeList[1] |
|
|
972 | 971 | profileList = list(range(minIndex, maxIndex+1)) |
|
|
973 | 972 | |
|
|
974 | 973 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
|
975 | 974 | |
|
|
976 | 975 | if rangeList != None: |
|
|
977 | 976 | |
|
|
978 | 977 | profileList = [] |
|
|
979 | 978 | |
|
|
980 | 979 | for thisRange in rangeList: |
|
|
981 | 980 | minIndex = thisRange[0] |
|
|
982 | 981 | maxIndex = thisRange[1] |
|
|
983 | 982 | |
|
|
984 | 983 | profileList.extend(list(range(minIndex, maxIndex+1))) |
|
|
985 | 984 | |
|
|
986 | 985 | dataOut.data = dataOut.data[:,profileList,:] |
|
|
987 | 986 | |
|
|
988 | 987 | dataOut.nProfiles = len(profileList) |
|
|
989 | 988 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
|
990 | 989 | dataOut.flagNoData = False |
|
|
991 | 990 | |
|
|
992 | 991 | return dataOut |
|
|
993 | 992 | |
|
|
994 | 993 | """ |
|
|
995 | 994 | data dimension = [nChannels, nHeis] |
|
|
996 | 995 | """ |
|
|
997 | 996 | |
|
|
998 | 997 | if profileList != None: |
|
|
999 | 998 | |
|
|
1000 | 999 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
|
1001 | 1000 | |
|
|
1002 | 1001 | self.nProfiles = len(profileList) |
|
|
1003 | 1002 | dataOut.nProfiles = self.nProfiles |
|
|
1004 | 1003 | dataOut.profileIndex = self.profileIndex |
|
|
1005 | 1004 | dataOut.flagNoData = False |
|
|
1006 | 1005 | |
|
|
1007 | 1006 | self.incProfileIndex() |
|
|
1008 | 1007 | return dataOut |
|
|
1009 | 1008 | |
|
|
1010 | 1009 | if profileRangeList != None: |
|
|
1011 | 1010 | |
|
|
1012 | 1011 | minIndex = profileRangeList[0] |
|
|
1013 | 1012 | maxIndex = profileRangeList[1] |
|
|
1014 | 1013 | |
|
|
1015 | 1014 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
|
1016 | 1015 | |
|
|
1017 | 1016 | self.nProfiles = maxIndex - minIndex + 1 |
|
|
1018 | 1017 | dataOut.nProfiles = self.nProfiles |
|
|
1019 | 1018 | dataOut.profileIndex = self.profileIndex |
|
|
1020 | 1019 | dataOut.flagNoData = False |
|
|
1021 | 1020 | |
|
|
1022 | 1021 | self.incProfileIndex() |
|
|
1023 | 1022 | return dataOut |
|
|
1024 | 1023 | |
|
|
1025 | 1024 | if rangeList != None: |
|
|
1026 | 1025 | |
|
|
1027 | 1026 | nProfiles = 0 |
|
|
1028 | 1027 | |
|
|
1029 | 1028 | for thisRange in rangeList: |
|
|
1030 | 1029 | minIndex = thisRange[0] |
|
|
1031 | 1030 | maxIndex = thisRange[1] |
|
|
1032 | 1031 | |
|
|
1033 | 1032 | nProfiles += maxIndex - minIndex + 1 |
|
|
1034 | 1033 | |
|
|
1035 | 1034 | for thisRange in rangeList: |
|
|
1036 | 1035 | |
|
|
1037 | 1036 | minIndex = thisRange[0] |
|
|
1038 | 1037 | maxIndex = thisRange[1] |
|
|
1039 | 1038 | |
|
|
1040 | 1039 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
|
1041 | 1040 | |
|
|
1042 | 1041 | self.nProfiles = nProfiles |
|
|
1043 | 1042 | dataOut.nProfiles = self.nProfiles |
|
|
1044 | 1043 | dataOut.profileIndex = self.profileIndex |
|
|
1045 | 1044 | dataOut.flagNoData = False |
|
|
1046 | 1045 | |
|
|
1047 | 1046 | self.incProfileIndex() |
|
|
1048 | 1047 | |
|
|
1049 | 1048 | break |
|
|
1050 | 1049 | |
|
|
1051 | 1050 | return dataOut |
|
|
1052 | 1051 | |
|
|
1053 | 1052 | |
|
|
1054 | 1053 | if beam != None: #beam is only for AMISR data |
|
|
1055 | 1054 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
|
1056 | 1055 | dataOut.flagNoData = False |
|
|
1057 | 1056 | dataOut.profileIndex = self.profileIndex |
|
|
1058 | 1057 | |
|
|
1059 | 1058 | self.incProfileIndex() |
|
|
1060 | 1059 | |
|
|
1061 | 1060 | return dataOut |
|
|
1062 | 1061 | |
|
|
1063 | 1062 | raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter") |
|
|
1064 | 1063 | |
|
|
1065 | 1064 | |
|
|
1066 | 1065 | class Reshaper(Operation): |
|
|
1067 | 1066 | |
|
|
1068 | 1067 | def __init__(self, **kwargs): |
|
|
1069 | 1068 | |
|
|
1070 | 1069 | Operation.__init__(self, **kwargs) |
|
|
1071 | 1070 | |
|
|
1072 | 1071 | self.__buffer = None |
|
|
1073 | 1072 | self.__nitems = 0 |
|
|
1074 | 1073 | |
|
|
1075 | 1074 | def __appendProfile(self, dataOut, nTxs): |
|
|
1076 | 1075 | |
|
|
1077 | 1076 | if self.__buffer is None: |
|
|
1078 | 1077 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
|
1079 | 1078 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
|
1080 | 1079 | |
|
|
1081 | 1080 | ini = dataOut.nHeights * self.__nitems |
|
|
1082 | 1081 | end = ini + dataOut.nHeights |
|
|
1083 | 1082 | |
|
|
1084 | 1083 | self.__buffer[:, ini:end] = dataOut.data |
|
|
1085 | 1084 | |
|
|
1086 | 1085 | self.__nitems += 1 |
|
|
1087 | 1086 | |
|
|
1088 | 1087 | return int(self.__nitems*nTxs) |
|
|
1089 | 1088 | |
|
|
1090 | 1089 | def __getBuffer(self): |
|
|
1091 | 1090 | |
|
|
1092 | 1091 | if self.__nitems == int(1./self.__nTxs): |
|
|
1093 | 1092 | |
|
|
1094 | 1093 | self.__nitems = 0 |
|
|
1095 | 1094 | |
|
|
1096 | 1095 | return self.__buffer.copy() |
|
|
1097 | 1096 | |
|
|
1098 | 1097 | return None |
|
|
1099 | 1098 | |
|
|
1100 | 1099 | def __checkInputs(self, dataOut, shape, nTxs): |
|
|
1101 | 1100 | |
|
|
1102 | 1101 | if shape is None and nTxs is None: |
|
|
1103 | 1102 | raise ValueError("Reshaper: shape of factor should be defined") |
|
|
1104 | 1103 | |
|
|
1105 | 1104 | if nTxs: |
|
|
1106 | 1105 | if nTxs < 0: |
|
|
1107 | 1106 | raise ValueError("nTxs should be greater than 0") |
|
|
1108 | 1107 | |
|
|
1109 | 1108 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
|
1110 | 1109 | raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs))) |
|
|
1111 | 1110 | |
|
|
1112 | 1111 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
|
1113 | 1112 | |
|
|
1114 | 1113 | return shape, nTxs |
|
|
1115 | 1114 | |
|
|
1116 | 1115 | if len(shape) != 2 and len(shape) != 3: |
|
|
1117 | 1116 | raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights)) |
|
|
1118 | 1117 | |
|
|
1119 | 1118 | if len(shape) == 2: |
|
|
1120 | 1119 | shape_tuple = [dataOut.nChannels] |
|
|
1121 | 1120 | shape_tuple.extend(shape) |
|
|
1122 | 1121 | else: |
|
|
1123 | 1122 | shape_tuple = list(shape) |
|
|
1124 | 1123 | |
|
|
1125 | 1124 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
|
1126 | 1125 | |
|
|
1127 | 1126 | return shape_tuple, nTxs |
|
|
1128 | 1127 | |
|
|
1129 | 1128 | def run(self, dataOut, shape=None, nTxs=None): |
|
|
1130 | 1129 | |
|
|
1131 | 1130 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
|
1132 | 1131 | |
|
|
1133 | 1132 | dataOut.flagNoData = True |
|
|
1134 | 1133 | profileIndex = None |
|
|
1135 | 1134 | |
|
|
1136 | 1135 | if dataOut.flagDataAsBlock: |
|
|
1137 | 1136 | |
|
|
1138 | 1137 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
|
1139 | 1138 | dataOut.flagNoData = False |
|
|
1140 | 1139 | |
|
|
1141 | 1140 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
|
1142 | 1141 | |
|
|
1143 | 1142 | else: |
|
|
1144 | 1143 | |
|
|
1145 | 1144 | if self.__nTxs < 1: |
|
|
1146 | 1145 | |
|
|
1147 | 1146 | self.__appendProfile(dataOut, self.__nTxs) |
|
|
1148 | 1147 | new_data = self.__getBuffer() |
|
|
1149 | 1148 | |
|
|
1150 | 1149 | if new_data is not None: |
|
|
1151 | 1150 | dataOut.data = new_data |
|
|
1152 | 1151 | dataOut.flagNoData = False |
|
|
1153 | 1152 | |
|
|
1154 | 1153 | profileIndex = dataOut.profileIndex*nTxs |
|
|
1155 | 1154 | |
|
|
1156 | 1155 | else: |
|
|
1157 | 1156 | raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)") |
|
|
1158 | 1157 | |
|
|
1159 | 1158 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1160 | 1159 | |
|
|
1161 | 1160 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
|
1162 | 1161 | |
|
|
1163 | 1162 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
|
1164 | 1163 | |
|
|
1165 | 1164 | dataOut.profileIndex = profileIndex |
|
|
1166 | 1165 | |
|
|
1167 | 1166 | dataOut.ippSeconds /= self.__nTxs |
|
|
1168 | 1167 | |
|
|
1169 | 1168 | return dataOut |
|
|
1170 | 1169 | |
|
|
1171 | 1170 | class SplitProfiles(Operation): |
|
|
1172 | 1171 | |
|
|
1173 | 1172 | def __init__(self, **kwargs): |
|
|
1174 | 1173 | |
|
|
1175 | 1174 | Operation.__init__(self, **kwargs) |
|
|
1176 | 1175 | |
|
|
1177 | 1176 | def run(self, dataOut, n): |
|
|
1178 | 1177 | |
|
|
1179 | 1178 | dataOut.flagNoData = True |
|
|
1180 | 1179 | profileIndex = None |
|
|
1181 | 1180 | |
|
|
1182 | 1181 | if dataOut.flagDataAsBlock: |
|
|
1183 | 1182 | |
|
|
1184 | 1183 | #nchannels, nprofiles, nsamples |
|
|
1185 | 1184 | shape = dataOut.data.shape |
|
|
1186 | 1185 | |
|
|
1187 | 1186 | if shape[2] % n != 0: |
|
|
1188 | 1187 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2])) |
|
|
1189 | ||
|
|
1188 | ||
|
|
1190 | 1189 | new_shape = shape[0], shape[1]*n, int(shape[2]/n) |
|
|
1191 | ||
|
|
1190 | ||
|
|
1192 | 1191 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
|
1193 | 1192 | dataOut.flagNoData = False |
|
|
1194 | 1193 | |
|
|
1195 | 1194 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
|
1196 | 1195 | |
|
|
1197 | 1196 | else: |
|
|
1198 | 1197 | |
|
|
1199 | 1198 | raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)") |
|
|
1200 | 1199 | |
|
|
1201 | 1200 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1202 | 1201 | |
|
|
1203 | 1202 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
|
1204 | 1203 | |
|
|
1205 | 1204 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
|
1206 | 1205 | |
|
|
1207 | 1206 | dataOut.profileIndex = profileIndex |
|
|
1208 | 1207 | |
|
|
1209 | 1208 | dataOut.ippSeconds /= n |
|
|
1210 | 1209 | |
|
|
1211 | 1210 | return dataOut |
|
|
1212 | 1211 | |
|
|
1213 | 1212 | class CombineProfiles(Operation): |
|
|
1214 | 1213 | def __init__(self, **kwargs): |
|
|
1215 | 1214 | |
|
|
1216 | 1215 | Operation.__init__(self, **kwargs) |
|
|
1217 | 1216 | |
|
|
1218 | 1217 | self.__remData = None |
|
|
1219 | 1218 | self.__profileIndex = 0 |
|
|
1220 | 1219 | |
|
|
1221 | 1220 | def run(self, dataOut, n): |
|
|
1222 | 1221 | |
|
|
1223 | 1222 | dataOut.flagNoData = True |
|
|
1224 | 1223 | profileIndex = None |
|
|
1225 | 1224 | |
|
|
1226 | 1225 | if dataOut.flagDataAsBlock: |
|
|
1227 | 1226 | |
|
|
1228 | 1227 | #nchannels, nprofiles, nsamples |
|
|
1229 | 1228 | shape = dataOut.data.shape |
|
|
1230 | 1229 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
|
1231 | 1230 | |
|
|
1232 | 1231 | if shape[1] % n != 0: |
|
|
1233 | 1232 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1])) |
|
|
1234 | 1233 | |
|
|
1235 | 1234 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
|
1236 | 1235 | dataOut.flagNoData = False |
|
|
1237 | 1236 | |
|
|
1238 | 1237 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
|
1239 | 1238 | |
|
|
1240 | 1239 | else: |
|
|
1241 | 1240 | |
|
|
1242 | 1241 | #nchannels, nsamples |
|
|
1243 | 1242 | if self.__remData is None: |
|
|
1244 | 1243 | newData = dataOut.data |
|
|
1245 | 1244 | else: |
|
|
1246 | 1245 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
|
1247 | 1246 | |
|
|
1248 | 1247 | self.__profileIndex += 1 |
|
|
1249 | 1248 | |
|
|
1250 | 1249 | if self.__profileIndex < n: |
|
|
1251 | 1250 | self.__remData = newData |
|
|
1252 | 1251 | #continue |
|
|
1253 | 1252 | return |
|
|
1254 | 1253 | |
|
|
1255 | 1254 | self.__profileIndex = 0 |
|
|
1256 | 1255 | self.__remData = None |
|
|
1257 | 1256 | |
|
|
1258 | 1257 | dataOut.data = newData |
|
|
1259 | 1258 | dataOut.flagNoData = False |
|
|
1260 | 1259 | |
|
|
1261 | 1260 | profileIndex = dataOut.profileIndex/n |
|
|
1262 | 1261 | |
|
|
1263 | 1262 | |
|
|
1264 | 1263 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1265 | 1264 | |
|
|
1266 | 1265 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
|
1267 | 1266 | |
|
|
1268 | 1267 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
|
1269 | 1268 | |
|
|
1270 | 1269 | dataOut.profileIndex = profileIndex |
|
|
1271 | 1270 | |
|
|
1272 | 1271 | dataOut.ippSeconds *= n |
|
|
1273 | 1272 | |
|
|
1274 | 1273 | return dataOut |
|
|
1274 | ||
|
|
1275 | class PulsePairVoltage(Operation): | |
|
|
1276 | ''' | |
|
|
1277 | Function PulsePair(Signal Power, Velocity) | |
|
|
1278 | The real component of Lag[0] provides Intensity Information | |
|
|
1279 | The imag component of Lag[1] Phase provides Velocity Information | |
|
|
1280 | ||
|
|
1281 | Configuration Parameters: | |
|
|
1282 | nPRF = Number of Several PRF | |
|
|
1283 | theta = Degree Azimuth angel Boundaries | |
|
|
1284 | ||
|
|
1285 | Input: | |
|
|
1286 | self.dataOut | |
|
|
1287 | lag[N] | |
|
|
1288 | Affected: | |
|
|
1289 | self.dataOut.spc | |
|
|
1290 | ''' | |
|
|
1291 | isConfig = False | |
|
|
1292 | __profIndex = 0 | |
|
|
1293 | __initime = None | |
|
|
1294 | __lastdatatime = None | |
|
|
1295 | __buffer = None | |
|
|
1296 | __buffer2 = [] | |
|
|
1297 | __buffer3 = None | |
|
|
1298 | __dataReady = False | |
|
|
1299 | n = None | |
|
|
1300 | __nch = 0 | |
|
|
1301 | __nHeis = 0 | |
|
|
1302 | removeDC = False | |
|
|
1303 | ipp = None | |
|
|
1304 | lambda_ = 0 | |
|
|
1305 | ||
|
|
1306 | def __init__(self,**kwargs): | |
|
|
1307 | Operation.__init__(self,**kwargs) | |
|
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1308 | ||
|
|
1309 | def setup(self, dataOut, n = None, removeDC=False): | |
|
|
1310 | ''' | |
|
|
1311 | n= Numero de PRF's de entrada | |
|
|
1312 | ''' | |
|
|
1313 | self.__initime = None | |
|
|
1314 | self.__lastdatatime = 0 | |
|
|
1315 | self.__dataReady = False | |
|
|
1316 | self.__buffer = 0 | |
|
|
1317 | self.__buffer2 = [] | |
|
|
1318 | self.__buffer3 = 0 | |
|
|
1319 | self.__profIndex = 0 | |
|
|
1320 | ||
|
|
1321 | self.__nch = dataOut.nChannels | |
|
|
1322 | self.__nHeis = dataOut.nHeights | |
|
|
1323 | self.removeDC = removeDC | |
|
|
1324 | self.lambda_ = 3.0e8/(9345.0e6) | |
|
|
1325 | self.ippSec = dataOut.ippSeconds | |
|
|
1326 | self.nCohInt = dataOut.nCohInt | |
|
|
1327 | print("IPPseconds",dataOut.ippSeconds) | |
|
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1328 | ||
|
|
1329 | print("ELVALOR DE n es:", n) | |
|
|
1330 | if n == None: | |
|
|
1331 | raise ValueError("n should be specified.") | |
|
|
1332 | ||
|
|
1333 | if n != None: | |
|
|
1334 | if n<2: | |
|
|
1335 | raise ValueError("n should be greater than 2") | |
|
|
1336 | ||
|
|
1337 | self.n = n | |
|
|
1338 | self.__nProf = n | |
|
|
1339 | ||
|
|
1340 | self.__buffer = numpy.zeros((dataOut.nChannels, | |
|
|
1341 | n, | |
|
|
1342 | dataOut.nHeights), | |
|
|
1343 | dtype='complex') | |
|
|
1344 | ||
|
|
1345 | def putData(self,data): | |
|
|
1346 | ''' | |
|
|
1347 | Add a profile to he __buffer and increase in one the __profiel Index | |
|
|
1348 | ''' | |
|
|
1349 | self.__buffer[:,self.__profIndex,:]= data | |
|
|
1350 | self.__profIndex += 1 | |
|
|
1351 | return | |
|
|
1352 | ||
|
|
1353 | def pushData(self): | |
|
|
1354 | ''' | |
|
|
1355 | Return the PULSEPAIR and the profiles used in the operation | |
|
|
1356 | Affected : self.__profileIndex | |
|
|
1357 | ''' | |
|
|
1358 | ||
|
|
1359 | if self.removeDC==True: | |
|
|
1360 | mean = numpy.mean(self.__buffer,1) | |
|
|
1361 | tmp = mean.reshape(self.__nch,1,self.__nHeis) | |
|
|
1362 | dc= numpy.tile(tmp,[1,self.__nProf,1]) | |
|
|
1363 | self.__buffer = self.__buffer - dc | |
|
|
1364 | ||
|
|
1365 | data_intensity = numpy.sum(self.__buffer*numpy.conj(self.__buffer),1)/(self.n*self.nCohInt)#*self.nCohInt) | |
|
|
1366 | pair1 = self.__buffer[:,1:,:]*numpy.conjugate(self.__buffer[:,:-1,:]) | |
|
|
1367 | angle = numpy.angle(numpy.sum(pair1,1))*180/(math.pi) | |
|
|
1368 | #print(angle.shape)#print("__ANGLE__") #print("angle",angle[:,:10]) | |
|
|
1369 | data_velocity = (self.lambda_/(4*math.pi*self.ippSec))*numpy.angle(numpy.sum(pair1,1))#self.ippSec*self.nCohInt | |
|
|
1370 | n = self.__profIndex | |
|
|
1371 | ||
|
|
1372 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') | |
|
|
1373 | self.__profIndex = 0 | |
|
|
1374 | return data_intensity,data_velocity,n | |
|
|
1375 | ||
|
|
1376 | def pulsePairbyProfiles(self,data): | |
|
|
1377 | ||
|
|
1378 | self.__dataReady = False | |
|
|
1379 | data_intensity = None | |
|
|
1380 | data_velocity = None | |
|
|
1381 | self.putData(data) | |
|
|
1382 | if self.__profIndex == self.n: | |
|
|
1383 | data_intensity, data_velocity, n = self.pushData() | |
|
|
1384 | self.__dataReady = True | |
|
|
1385 | ||
|
|
1386 | return data_intensity, data_velocity | |
|
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1387 | ||
|
|
1388 | def pulsePairOp(self, data, datatime= None): | |
|
|
1389 | ||
|
|
1390 | if self.__initime == None: | |
|
|
1391 | self.__initime = datatime | |
|
|
1392 | ||
|
|
1393 | data_intensity, data_velocity = self.pulsePairbyProfiles(data) | |
|
|
1394 | self.__lastdatatime = datatime | |
|
|
1395 | ||
|
|
1396 | if data_intensity is None: | |
|
|
1397 | return None, None, None | |
|
|
1398 | ||
|
|
1399 | avgdatatime = self.__initime | |
|
|
1400 | deltatime = datatime - self.__lastdatatime | |
|
|
1401 | self.__initime = datatime | |
|
|
1402 | ||
|
|
1403 | return data_intensity, data_velocity, avgdatatime | |
|
|
1404 | ||
|
|
1405 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): | |
|
|
1406 | ||
|
|
1407 | if not self.isConfig: | |
|
|
1408 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) | |
|
|
1409 | self.isConfig = True | |
|
|
1410 | data_intensity, data_velocity, avgdatatime = self.pulsePairOp(dataOut.data, dataOut.utctime) | |
|
|
1411 | dataOut.flagNoData = True | |
|
|
1412 | ||
|
|
1413 | if self.__dataReady: | |
|
|
1414 | dataOut.nCohInt *= self.n | |
|
|
1415 | dataOut.data_intensity = data_intensity #valor para intensidad | |
|
|
1416 | dataOut.data_velocity = data_velocity #valor para velocidad | |
|
|
1417 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. | |
|
|
1418 | dataOut.utctime = avgdatatime | |
|
|
1419 | dataOut.flagNoData = False | |
|
|
1420 | return dataOut | |
|
|
1421 | ||
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1422 | ||
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|
1275 | 1423 | # import collections |
|
|
1276 | 1424 | # from scipy.stats import mode |
|
|
1277 | 1425 | # |
|
|
1278 | 1426 | # class Synchronize(Operation): |
|
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1279 | 1427 | # |
|
|
1280 | 1428 | # isConfig = False |
|
|
1281 | 1429 | # __profIndex = 0 |
|
|
1282 | 1430 | # |
|
|
1283 | 1431 | # def __init__(self, **kwargs): |
|
|
1284 | 1432 | # |
|
|
1285 | 1433 | # Operation.__init__(self, **kwargs) |
|
|
1286 | 1434 | # # self.isConfig = False |
|
|
1287 | 1435 | # self.__powBuffer = None |
|
|
1288 | 1436 | # self.__startIndex = 0 |
|
|
1289 | 1437 | # self.__pulseFound = False |
|
|
1290 | 1438 | # |
|
|
1291 | 1439 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
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1292 | 1440 | # |
|
|
1293 | 1441 | # #Read data |
|
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1294 | 1442 | # |
|
|
1295 | 1443 | # powerdB = dataOut.getPower(channel = channel) |
|
|
1296 | 1444 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
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1297 | 1445 | # |
|
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1298 | 1446 | # self.__powBuffer.extend(powerdB.flatten()) |
|
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1299 | 1447 | # |
|
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1300 | 1448 | # dataArray = numpy.array(self.__powBuffer) |
|
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1301 | 1449 | # |
|
|
1302 | 1450 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
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1303 | 1451 | # |
|
|
1304 | 1452 | # maxValue = numpy.nanmax(filteredPower) |
|
|
1305 | 1453 | # |
|
|
1306 | 1454 | # if maxValue < noisedB + 10: |
|
|
1307 | 1455 | # #No se encuentra ningun pulso de transmision |
|
|
1308 | 1456 | # return None |
|
|
1309 | 1457 | # |
|
|
1310 | 1458 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
|
1311 | 1459 | # |
|
|
1312 | 1460 | # if len(maxValuesIndex) < 2: |
|
|
1313 | 1461 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
|
1314 | 1462 | # return None |
|
|
1315 | 1463 | # |
|
|
1316 | 1464 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
|
1317 | 1465 | # |
|
|
1318 | 1466 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
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1319 | 1467 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
|
1320 | 1468 | # |
|
|
1321 | 1469 | # if len(pulseIndex) < 2: |
|
|
1322 | 1470 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
|
1323 | 1471 | # return None |
|
|
1324 | 1472 | # |
|
|
1325 | 1473 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
|
1326 | 1474 | # |
|
|
1327 | 1475 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
|
1328 | 1476 | # #(No deberian existir IPP menor a 10 unidades) |
|
|
1329 | 1477 | # |
|
|
1330 | 1478 | # realIndex = numpy.where(spacing > 10 )[0] |
|
|
1331 | 1479 | # |
|
|
1332 | 1480 | # if len(realIndex) < 2: |
|
|
1333 | 1481 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
|
1334 | 1482 | # return None |
|
|
1335 | 1483 | # |
|
|
1336 | 1484 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
|
1337 | 1485 | # realPulseIndex = pulseIndex[realIndex] |
|
|
1338 | 1486 | # |
|
|
1339 | 1487 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
|
1340 | 1488 | # |
|
|
1341 | 1489 | # print "IPP = %d samples" %period |
|
|
1342 | 1490 | # |
|
|
1343 | 1491 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
|
1344 | 1492 | # self.__startIndex = int(realPulseIndex[0]) |
|
|
1345 | 1493 | # |
|
|
1346 | 1494 | # return 1 |
|
|
1347 | 1495 | # |
|
|
1348 | 1496 | # |
|
|
1349 | 1497 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
|
1350 | 1498 | # |
|
|
1351 | 1499 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
|
1352 | 1500 | # maxlen = buffer_size*nSamples) |
|
|
1353 | 1501 | # |
|
|
1354 | 1502 | # bufferList = [] |
|
|
1355 | 1503 | # |
|
|
1356 | 1504 | # for i in range(nChannels): |
|
|
1357 | 1505 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
|
1358 | 1506 | # maxlen = buffer_size*nSamples) |
|
|
1359 | 1507 | # |
|
|
1360 | 1508 | # bufferList.append(bufferByChannel) |
|
|
1361 | 1509 | # |
|
|
1362 | 1510 | # self.__nSamples = nSamples |
|
|
1363 | 1511 | # self.__nChannels = nChannels |
|
|
1364 | 1512 | # self.__bufferList = bufferList |
|
|
1365 | 1513 | # |
|
|
1366 | 1514 | # def run(self, dataOut, channel = 0): |
|
|
1367 | 1515 | # |
|
|
1368 | 1516 | # if not self.isConfig: |
|
|
1369 | 1517 | # nSamples = dataOut.nHeights |
|
|
1370 | 1518 | # nChannels = dataOut.nChannels |
|
|
1371 | 1519 | # self.setup(nSamples, nChannels) |
|
|
1372 | 1520 | # self.isConfig = True |
|
|
1373 | 1521 | # |
|
|
1374 | 1522 | # #Append new data to internal buffer |
|
|
1375 | 1523 | # for thisChannel in range(self.__nChannels): |
|
|
1376 | 1524 | # bufferByChannel = self.__bufferList[thisChannel] |
|
|
1377 | 1525 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
|
1378 | 1526 | # |
|
|
1379 | 1527 | # if self.__pulseFound: |
|
|
1380 | 1528 | # self.__startIndex -= self.__nSamples |
|
|
1381 | 1529 | # |
|
|
1382 | 1530 | # #Finding Tx Pulse |
|
|
1383 | 1531 | # if not self.__pulseFound: |
|
|
1384 | 1532 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
|
1385 | 1533 | # |
|
|
1386 | 1534 | # if indexFound == None: |
|
|
1387 | 1535 | # dataOut.flagNoData = True |
|
|
1388 | 1536 | # return |
|
|
1389 | 1537 | # |
|
|
1390 | 1538 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
|
1391 | 1539 | # self.__pulseFound = True |
|
|
1392 | 1540 | # self.__startIndex = indexFound |
|
|
1393 | 1541 | # |
|
|
1394 | 1542 | # #If pulse was found ... |
|
|
1395 | 1543 | # for thisChannel in range(self.__nChannels): |
|
|
1396 | 1544 | # bufferByChannel = self.__bufferList[thisChannel] |
|
|
1397 | 1545 | # #print self.__startIndex |
|
|
1398 | 1546 | # x = numpy.array(bufferByChannel) |
|
|
1399 | 1547 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
|
1400 | 1548 | # |
|
|
1401 | 1549 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1402 | 1550 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
|
1403 | 1551 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
|
1404 | 1552 | # |
|
|
1405 | 1553 | # dataOut.data = self.__arrayBuffer |
|
|
1406 | 1554 | # |
|
|
1407 | 1555 | # self.__startIndex += self.__newNSamples |
|
|
1408 | 1556 | # |
|
|
1409 | 1557 | # return |
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